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Objectives The Kidney Team at Home program is an educational intervention aimed at patients with chronic kidney disease to assist them in their choice for kidney replacement therapy. Previous studies have shown that the intervention results in an increase in knowledge and communication on kidney replacement therapy, and eventually in an increase in the number of living donor kidney transplantations. The study assesses the cost-effectiveness of the intervention compared to standard care. Methods A dynamic probabilistic Markov model was used to estimate the monetary and health benefits of the intervention in The Netherlands over 10 years. Data on costs and health-related quality of life were derived from the literature. Transition probabilities, prevalence, and incidence rates were calculated using a large national database. An optimistic and a pessimistic implementation scenario were compared to a base case scenario with standard care. Results In both the optimistic and pessimistic scenario, the intervention is cost-effective and dominant compared to standard care: savings were €108,681,985 and €51,770,060 and the benefits were 1382 and 695 QALYs, respectively. Conclusions The superior cost-effectiveness of the intervention is caused by the superior health effects and the reduction of costs associated with transplantation, and the relatively small incremental costs of the intervention. The favorable findings of this implementation project resulted in national uptake of the intervention in The Netherlands as of 2021. This is the first time a psychosocial intervention has been implemented as part of standard care in a kidney replacement therapy program worldwide.

Adjuvant chemotherapy is not recommended for patients with average-risk stage II (T3N0) colon cancer. Nevertheless, a subgroup of these patients who are CDX2-negative might benefit from adjuvant chemotherapy. We evaluated the cost-effectiveness of testing for the absence of CDX2 expression followed by adjuvant chemotherapy (fluorouracil combined with oxaliplatin [FOLFOX]) for patients with stage II colon cancer.We developed a decision model to simulate a hypothetical cohort of 65-year-old patients with average-risk stage II colon cancer with 7.2% of these patients being CDX2-negative under 2 different interventions: (1) test for the absence of CDX2 expression followed by adjuvant chemotherapy for CDX2-negative patients and (2) no CDX2 testing and no adjuvant chemotherapy for any patient. We derived disease progression parameters, adjuvant chemotherapy effectiveness and utilities from published analyses, and cancer care costs from the Surveillance, Epidemiology, and End Results (SEER)-Medicare data. Sensitivity analyses were conducted.Testing for CDX2 followed by FOLFOX for CDX2-negative patients had an incremental cost-effectiveness ratio of $5500/quality-adjusted life-years (QALYs) compared with no CDX2 testing and no FOLFOX (6.874 vs 6.838 discounted QALYs and $89 991 vs $89 797 discounted US dollar lifetime costs). In sensitivity analyses, considering a cost-effectiveness threshold of $100 000/QALY, testing for CDX2 followed by FOLFOX on CDX2-negative patients remains cost-effective for hazard ratios of0.975 of the effectiveness of FOLFOX in CDX2-negative patients in reducing the rate of developing a metastatic recurrence.Testing tumors of patients with stage II colon cancer for CDX2 and administration of adjuvant treatment to the subgroup found CDX2-negative is a cost-effective and high-value management strategy across a broad range of plausible assumptions.

Objectives The purpose of this study was to evaluate the cost-effectiveness of nab-paclitaxel and gemcitabine (GnP) compared with gemcitabine monotherapy (G) for patients with unresectable metastatic pancreatic cancer in Japan from the perspective of healthcare payer. Methods A partitioned survival analysis model was developed to predict costs and quality-adjusted life years (QALYs) for GnP and G. The time horizon of the model was set at 20 years. An annual discount rate of 2% for both costs and QALYs was applied. Data on overall survival and progression-free survival were derived from the Metastatic Pancreatic Adenocarcinoma Clinical Trial. Cost parameters were estimated from a Japanese medical claims database. The incremental cost-effectiveness ratio (ICER) of GnP compared with G was estimated. One-way sensitivity analysis was performed to assess the uncertainty in the parameter settings. In addition, scenario and probability sensitivity analyses were performed. Results The incremental cost and QALY of GnP compared with G were US$25 089 and 0.13 QALY, respectively. The ICER of GnP was estimated to be US$192 992 per QALY gained. Although the ICER was influenced by utility parameters and the survival curves, the ICERs remained higher than the willingness to pay (WTP) threshold of US$68 000 (JPY 7.5 million). The probability that GnP becomes cost-effective compared with G was estimated to be 29.2%. Conclusions Applying the WTP threshold of US$68 000 per QALY, GnP was not cost-effective for patients with unresectable metastatic pancreatic cancer in Japan from the perspective of healthcare payer. Further research is needed to obtain utility data from Japanese patients with pancreatic cancer.

An ongoing debate exists over the optimal management of low-risk papillary thyroid cancer. The American Thyroid Association supports the concept of active surveillance to manage low-risk papillary thyroid cancer; however, the cost-effectiveness of active surveillance has not yet been established. We sought to perform a cost-effectiveness analysis comparing active surveillance versus surgical intervention for patients in the United States.A Markov decision tree model was developed to compare active surveillance and thyroid lobectomy. Our reference case is a 40-year-old female who was diagnosed with unifocal (15 mm), low-risk papillary thyroid cancer. Probabilistic outcomes, costs, and health utilities were determined using an extensive literature review. The willingness-to-pay threshold was set at $50,000/quality-adjusted life year gained. Sensitivity analyses were performed to account for uncertainty in the model's variables.Lobectomy provided a final effectiveness of 21.7/quality-adjusted life years, compared with 17.3/quality-adjusted life years for active surveillance. Furthermore, incremental cost effectiveness ratio for lobectomy versus active surveillance was $19,560/quality-adjusted life year (willing-to-pay threshold of $50,000/quality-adjusted life year), and thus surgical intervention proved to be cost-effective in patients between 40 and 69 years old. Further analysis revealed that, at the age of 69 years, active surveillance is more cost-effective than lobectomy, with a final effectiveness of 17.3/quality-adjusted life years. Compared to active surveillance, the incremental cost effectiveness ratio for lobectomy at the age of 69 was $27,235/quality-adjusted life year, which decreases quality-adjusted life years by 1.5.Lobectomy is a cost-effective strategy in middle-aged patients with low-risk papillary thyroid cancer. In contrast, active surveillance is cost-effective beginning at the age of 69. Identification of such nuances can help physicians and patients determine the best, most individualized long-term management strategy for low-risk papillary thyroid cancer.

Summary Background India faces a high burden of diabetes and hypertension. Currently, there is a dearth of economic evidence about screening programmes, affected age groups, and frequency of screening for these diseases in Indian settings. We assessed the cost effectiveness of population-based screening for diabetes and hypertension compared with current practice in India for different scenarios, according to type of screening test, population age group, and pattern of health-care use. Methods We used a hybrid decision model (decision tree and Markov model) to estimate the lifetime costs and consequences from a societal perspective. A meta-analysis was done to assess the effectiveness of population-based screening. Primary data were collected from two Indian states (Haryana and Tamil Nadu) to assess the cost of screening. The data from the National Health System Cost Database and the Costing of Health Services in India study were used to determine the health system cost of diagnostic tests and cost of treating diabetes or hypertension and their complications. A total of 962 patients were recruited to assess out-of-pocket expenditure and quality of life. Parameter uncertainty was evaluated using univariate and multivariable probabilistic sensitivity analyses. Finally, we estimated the incremental cost per quality-adjusted life-year (QALY) gained with alternative scenarios of scaling up primary health care through a health and wellness centre programme for the treatment of diabetes and hypertension. Findings The incremental cost per QALY gained across various strategies for population-based screening for diabetes and hypertension ranged from US$0·02 million to $0·03 million. At the current pattern of health services use, none of the screening strategies of annual screening, screening every 3 years, and screening every 5 years was cost-effective at a threshold of 1-time per capita gross domestic product in India. In the scenario in which health and wellness centres provided primary care to 20% of patients who were newly diagnosed with uncomplicated diabetes or hypertension, screening the group aged between 30 and 65 years every 5 years or 3 years for either diabetes, hypertension, or a comorbid state (both diabetes and hypertension) became cost-effective. If the share of treatment for patients with newly diagnosed uncomplicated diabetes or hypertension at health and wellness centres increases to 70%, from the existing 4% at subcentres and primary health centres, annual population-based screening becomes a cost saving strategy. Interpretation Population-based screening for diabetes and hypertension in India could potentially reduce time to diagnosis and treatment and be cost-effective if it is linked to comprehensive primary health care through health and wellness centres for provision of treatment to patients who screen positive. Funding Department of Health Research, Government of India.

PURPOSE The COVID-19 pandemic has placed unprecedented demands on the health system. This led to delays in the initiation and completion of cancer treatment. We assessed the long-term health consequences because of the delay in diagnosis and treatment for cervical cancer due to COVID-19 in India. METHODS We used a Markov-model–based analysis assessing the lifetime health outcomes of the cohort of women population at risk from cervical cancer in India. The decrease in survival for those with the treatment interruption was calculated based on the number of days the treatment was extended beyond the standard duration. Furthermore, to model the impact of late diagnosis and delayed treatment initiation, the patients were assumed to have upstaged during the delay period, as per natural progression of disease. RESULTS We estimate 2.52% (n = 795) to 3.80% (n = 2,160) lifetime increase in the deaths caused by cervical cancer with treatment restrictions ranging from 9 weeks to 6 months, respectively, as compared to no delay. On the contrary, 88-238 deaths because of COVID-19 disease are estimated to be saved during this restriction period among the patients with cervical cancer. Overall, the excess mortality because of cervical cancer led to 18,159-53,626 life-years being lost and an increase of 16,808-50,035 disability-adjusted life-years. CONCLUSION Delays in diagnosis and treatment are likely to lead to more cervical cancer deaths as compared to COVID-19 mortality averted among the patients with cervical cancer. Health systems must reorganize in terms of priority setting for provision of care, starting with prioritizing the treatment of patients with early-stage cervical cancer, increasing use of teleconsultation, and strengthening the role of primary care physicians in provision of cancer care.

Aims Total hip arthroplasty (THA) with dual-mobility components (DM-THA) has been shown to decrease the risk of dislocation in the setting of a displaced neck of femur fracture compared to conventional single-bearing THA (SB-THA). This study assesses if the clinical benefit of a reduced dislocation rate can justify the incremental cost increase of DM-THA compared to SB-THA. Methods Costs and benefits were established for patients aged 75 to 79 years over a five-year time period in the base case from the Canadian Health Payer’s perspective. One-way and probabilistic sensitivity analysis assessed the robustness of the base case model conclusions. Results DM-THA was found to be cost-effective, with an estimated incremental cost-effectiveness ratio (ICER) of CAD $46,556 (£27,074) per quality-adjusted life year (QALY). Sensitivity analysis revealed DM-THA was not cost-effective across all age groups in the first two years. DM-THA becomes cost-effective for those aged under 80 years at time periods from five to 15 years, but was not cost-effective for those aged 80 years and over at any timepoint. To be cost-effective at ten years in the base case, DM-THA must reduce the risk of dislocation compared to SB-THA by at least 62%. Probabilistic sensitivity analysis showed DM-THA was 58% likely to be cost-effective in the base case. Conclusion Treating patients with a displaced femoral neck fracture using DM-THA components may be cost-effective compared to SB-THA in patients aged under 80 years. However, future research will help determine if the modelled rates of adverse events hold true. Surgeons should continue to use clinical judgement and consider individual patients’ physiological age and risk factors for dislocation. Cite this article: Bone Joint J 2021;103-B(12):1783–1790.

Objectives Real option value (ROV) is created when a drug enables a patient to live long enough to benefit from a future innovation. Few studies have quantified ROV in the real world. We aimed to estimate the ex post ROV for ipilimumab in metastatic melanoma using real-world data (RWD). Methods We developed a framework for calculating ROV using RWD, accounting for the health gain in the standard therapy arm and the uptake of future innovations. A Markov model was developed to estimate the quality-adjusted life-years (QALYs) gained with ipilimumab compared with chemotherapy for patients with or without subsequent cancer immunotherapy (CIT). A nationwide electronic health record-derived, deidentified database was used to estimate survival and uptake of CIT. Results The incremental QALYs gained for ipilimumab compared with chemotherapy without subsequent CIT were 1.74. With subsequent CIT, the incremental QALYs compared with chemotherapy increased by 0.92, 0.60, 0.33, 0.18, 0.10, and 0.02 when CIT became available 0, 3, 6, 9, 12, and 24 months after the initiation of first-line treatment, respectively. The results were most sensitive to the survival benefit of ipilimumab, the survival benefit of subsequent CIT, and the uptake of CIT. Conclusions This is the first study to estimate ex post ROV using RWD. The ex post ROV was between 1% and 54% of conventional value for patients who received a diagnosis within 2 years before CIT availability. Further studies are needed to understand ROV in other disease areas, particularly those with longer survival times.

BACKGROUND: Multiple myeloma survival rates are steadily increasing due to availability of new drug classes used in combination with corticosteroids and chemotherapy. The latest treatments are daratumumab or bortezomib in combination therapy with lenalidomide and dexamethasone (Rd). Daratumumab, a CD38-targeted, human IgG1k monoclonal antibody, and bortezomib, a proteasome inhibitor, are both approved as regimens for transplant-ineligible relapsed/refractory multiple myeloma (RRMM). There have been cost-effectiveness analyses for daratumumab and bortezomib use in RRMM, but there are limited data regarding cost-effectiveness for daratumumab or bortezomib use in newly diagnosed multiple myeloma patients who are ineligible for stem cell transplantation. OBJECTIVE: To compare the cost-effectiveness of 3 separate regimens-(1) daratumumab, lenalidomide, and dexamethasone triple therapy (DRd); (2) bortezomib and lenalidomide plus dexamethasone triple therapy (VRd); and (3) lenalidomide plus dexamethasone (Rd)-in patients with multiple myeloma ineligible for autologous stem cell transplant. METHODS: A 2-state Markov model was developed using a US health system perspective and lifetime time horizon. Transition probabilities were calculated from the latest progression-free survival data reported in two phase 3 randomized controlled trials-MAIA and SWOG S0777-and extrapolated using a Weibull distribution based on the Hoyle Henley method. National data sources were used to obtain costs in 2019 US dollars, discounted by 3%. Health state utilities from available literature were applied to each health state. Utility decrements for adverse events were individualized in each choice branch with utility decrement weighted by the percentage of patients who experienced the adverse event in the MAIA and SWOG S0777 trials. We assumed a treatment would be cost-effective at a willingness to pay (WTP) of $150,000 per progression-free quality-adjusted life-year ($/PFQALY). One-way and probabilistic sensitivity analyses were conducted. RESULTS: Rd standard therapy had the lowest overall cost at $329,867, followed by VRd at $385,434 and DRd with the highest overall total cost at $626,900. Rd was estimated to result in the least amount (1.24) of PFQALYs, followed by VRd at 1.35 PFQALYs and DRd at 1.52 PFQALYs. With a WTP threshold of $150,000 per PFQALY, VRd was not cost-effective compared with Rd standard therapy, with an incremental cost-effectiveness ratio (ICER) of $530,256 per PFQALY. DRd was not cost-effective compared with VRd (ICER = $1,396,318 per PFQALY), nor as compared with Rd standard therapy (ICER = $1060,832). One-way sensitivity analysis showed that our model was sensitive to cost of DRd, VRd, and Rd drugs. Probabilistic sensitivity analysis showed that only at a WTP threshold of $550,000 was VRd cost-effective for 40% of iterations. There were no reasonable WTP thresholds, up to $800,00, where DRd became more cost-effective than VRd. CONCLUSIONS: This study is the first analysis to directly compare the cost-effectiveness of 3 acceptable chemotherapy treatment regimens for patients with multiple myeloma ineligible for autologous stem cell transplant. Neither DRd nor VRd triple therapy were found to be cost-effective vs Rd. Further cost-effectiveness analyses that include overall survival data for daratumumab and bortezomib triple therapies are needed to demonstrate an ICER in QALYs. DISCLOSURES: No funding was received for this study. At the time of this study, Narsipur was a UCSF-Actelion Clinical Research and Medical Communications Fellow, unrelated to this study. The other authors have nothing to disclose.

Adeno-associated virus (AAV)-mediated gene therapy is a novel treatment promising to reduce morbidity associated with hemophilia. Although multiple clinical trials continue to evaluate efficacy and safety, limited cost-effectiveness data have been published. This study compared the potential cost-effectiveness of AAV-mediated factor IX (FIX)-Padua gene therapy for patients with severe hemophilia B in the United States vs on-demand FIX replacement and primary FIX prophylaxis, using either standard or extended half-life FIX products. A microsimulation Markov model was constructed, and transition probabilities between health states and utilities were informed by using published data. Costs were aggregated by using a microcosting approach. A time horizon from 18 years old until death, from the perspective of a third-party payer in the United States, was conducted. Gene therapy was more cost-effective than both alternatives considering a $150 000/quality-adjusted life-year threshold. The price for gene therapy was assumed to be $2 000 000 in the base case scenario; however, one of the 1-way sensitivity analyses was conducted by using observed manufacturing, administration, and 5-year follow-up costs of $87 198 for AAV-mediated gene therapy vector as derived from the manufacturing facility and clinical practice at St Jude Children’s Research Hospital. One-way sensitivity analyses revealed 10 of 102 scenarios in which gene therapy was not cost-effective compared with alternative treatments. Notably, gene therapy remained cost-effective in a hypothetical scenario in which we estimated that the discounted factor concentrate price was 20% of the wholesale acquisition cost in the United States. Probabilistic sensitivity analysis estimated gene therapy to be cost-effective at 92% of simulations considering a $150 000/quality-adjusted life-year threshold. In conclusion, based on detailed simulation inputs and assumptions, gene therapy was more cost-effective than on-demand treatment and prophylaxis for patients with severe hemophilia B.

International audience; OBJECTIVES: Patients waking up with stroke symptoms are often excluded from intravenous thrombolysis with alteplase (IV-tpa). The WAKE-UP trial, a European multicenter randomized controlled trial, proved the clinical effectiveness of magnetic resonance imaging-guided IV-tpa for these patients. This analysis aimed to assess the cost-effectiveness of the intervention compared to placebo. METHODS: A Markov model was designed to analyze the cost-effectiveness over a 25-year time horizon. The model consisted of an inpatient acute care phase and a rest-of-life phase. Health states were defined by the modified Rankin Scale (mRS). Initial transition probabilities to mRS scores were based on WAKE-UP data and health state utilities on literature search. Costs were based on data from the University Medical Center Hamburg-Eppendorf, literature, and expert opinion. Incremental costs and effects over the patients' lifetime were estimated. The analysis was conducted from a formal German healthcare perspective. Univariate and probabilistic sensitivity analyses were performed. RESULTS: Treatment with IV-tpa resulted in cost savings of €51 009 and 1.30 incremental gains in quality-adjusted life-years at a 5% discount rate. Univariate sensitivity analysis revealed incremental cost-effectiveness ratio being sensitive to the relative risk of favorable outcome on mRS for placebo patients after stroke, the costs of long-term care for patients with mRS 4, and patient age at initial stroke event. In all cases, IV-tpa remained cost-effective. Probabilistic sensitivity analysis proved IV-tpa cost-effective in \textgreater95% of the simulations results. CONCLUSIONS: Magnetic resonance imaging-guided IV-tpa compared to placebo is cost-effective in patients with ischemic stroke with unknown time of onset.

Background Breast cancer is the most common cancer diagnosed in women. Screening mammography is the only imaging screening study for breast cancer with a proven. mortality benefit. This study aims to analyze the cost-effectiveness of screening mammography in Ethiopia. Methods Multistate Markov model was used for computer simulation to estimate cost and health benefits of screening mammography interventions for age-group of 40–49 years and 50–59 years. The cost-effectiveness analysis was made for 4 policies based on where the screening mammography procedures were conducted: government institution only, the private institution only, 50% ratio for each, and 10% private institution policy. Outputs were expressed in total cost, life-years gained (LYG) incremental cost-effectiveness ratio (ICER), and incremental net monetary benefit (INMB). Results All 4 policies of annual screening mammography failed to achieve acceptable ICER and lead to a net loss in INMB. The lowest ICER value was for government institution-only policy with 3510.3 USD/LYG and 3224.9 USD/LYG both above the cost-effectiveness threshold of 2808.5 USD. The cost per single death averted for each group was 110,206.7 USD and 77,088.2 USD for age-group 40–49 years and 50–59 years respectively. Conclusion Screening mammography could not be shown to be cost-effective in Ethiopia with the current low cost-effectiveness threshold. Alternative screening approach like annual clinical breast examination may need to be investigated.

Objective The main objective of the economic evaluation was to determine the cost-effectiveness of a weaning-food safety and hygiene programme in reducing rates of diarrhoea compared to the control in rural Gambia. Methods The public health intervention, using critical control points and motivational drivers, was evaluated in a cluster randomised controlled trial at 6- and 32-month follow-up. An economic evaluation was undertaken alongside the RCT with data collected prospectively from a societal perspective. Decision-analytical modelling was used to explore cost-effectiveness over a longer time period (4 years). Results Direct out-of-pocket healthcare expenditure for households due to diarrhoea was large. The intervention significantly reduced reported childhood diarrhoeal episodes after six months (incident risk ratio =0.40, 95%CI 0.33, 0.49) and two years after the intervention (incident risk ratio = 0.68, 95%CI 0.46, 1.02). The within-trial analysis found that the intervention led to total savings of 8064 dalasi six months after the intervention, and 4224 dalasi two years after the intervention. Based on the model results, if the intervention is successful in maintaining the reduction in the risk of diarrhea, the ICER is US$ 814 per DALY avoided over 4 years. This is cost effective. Conclusions This study suggests that there are substantial household costs associated with diarrhoeal episodes in children. The within-trial analysis and model results suggest that the community-based approach to improving weaning food hygiene and safety is likely to be cost-effective compared to control.

Pneumonia is the main reason for mortality among children under five years, causing 1.6 million deaths every year; late research has exhibited that mortality is increasing in the elderly. A few biomarkers used for its diagnosis need specificity and precision, as they are related to different infections, for example, pulmonary tuberculosis and Human Immunodeficiency Virus. There is a quest for new biomarkers worldwide to diagnose the disease to defeat these previously mentioned constraints. Antimicrobial peptides (AMPs) are promising indicative specialists against infection. This research work used AMPs as biomarkers to detect viral pneumonia pathogens, for example, Respiratory syncytial virus, Influenza A and B viruses utilizing in silico technologies, such as Hidden Markov Model (HMMER). HMMER was used to distinguish putative anti-viral pneumonia AMPs against the recognized receptor proteins of Respiratory syncytial virus, Influenza A, and B viruses. The physicochemical parameters of these putative AMPs were analyzed, and their 3-D structures were determined utilizing I-TASSER. Molecular docking interaction of these AMPs against the recognized viral pneumonia proteins was carried out using the PATCHDOCK and HDock servers. The results demonstrated 27 anti-viral AMPs ranked based on their E values with significant physicochemical parameters in similarity with known experimentally approved AMPs. The AMPs additionally had a high anticipated binding potential to the pneumonia receptors of these microorganisms sensitively. The tendency of the putative anti-viral AMPs to bind pneumonia proteins showed that they would be promising applicant biomarkers to identify these viral microorganisms in the point-of-care (POC) pneumonia diagnostics. The high precision observed for the AMPs legitimizes HMM’s utilization in the disease diagnostics’ discovery process.

Background The optimal therapeutic strategies for patients with metastatic hormone-sensitive prostate cancer (mHSPC) followed by metastatic castrate-resistant prostate cancer (mCRPC), in terms of cost and effectiveness remains unknown. This study aims to compare the cost-effectiveness of various potential strategies, from the start of first-line treatment in mHSPC to the death of the patients. Methods Two Markov decision-analysis models were developed, one for cohort A “asymptomatic/mildly symptomatic patients in mCRPC” and one for cohort B “symptomatic patients in mCRPC”. Each strategy reflects daily practice for mHSPC until progression in mCRPC from the start of first treatment regimen with either docetaxel or abiraterone acetate plus prednisone (AA) in mHSPC to the death of the patient. The cost-effectiveness analysis was performed from the French public healthcare system perspective. Only direct medical costs were included. Survival data were extracted from results of published randomized clinical trials. Results For cohort A, docetaxel followed by AA is the most cost-effective therapeutic strategy (€96,925 for 4.24 life-years). For cohort B, docetaxel followed by docetaxel is the most cost-effective therapeutic strategy (€81,463 for 4.05 life-years). Sensitivity analyses confirmed the robustness of our results except for a price reduction of 70% for AA or enzalutamide. Conclusions Our approach is innovative to the extent that our analysis takes into account various potential strategies for mPC. Our economic evaluation suggests that a price reduction of AA or enzalutamide impacts on the results. This approach must continue, including new drugs for patients with mPC. MICRO-ABSTRACT This study aims to define optimal sequencing for patients moving from mHSPC to mCRPC based on their cost and effectiveness through literature publications. The results add useful information to clinician and patients facing treatment decisions in the real world.

Background With emerging evidence on the efficacy of adding dapagliflozin to standard care for patients with heart failure with reduced ejection fraction (HFrEF), this study assessed the cost-effectiveness of add-on dapagliflozin to standard care versus standard care alone for HFrEF from the perspective of healthcare systems in the Asia–Pacific region. Methods A Markov model was applied to project the outcomes of treatment in terms of lifetime medical cost and quality-adjusted life-years. The transition probabilities between health states in the model were obtained from the Dapagliflozin in Patients with Heart Failure and Reduced Ejection Fraction trial. Country-specific costs and utilities were extracted for modeling. The incremental cost-effectiveness ratio against a country-specific willingness-to-pay threshold was applied to determine the cost-effectiveness of treatment. A series of sensitivity analyses were performed to ensure the robustness of the study results. Costs are presented in 2020 United States dollars. Results The incremental cost-effectiveness ratios for add-on dapagliflozin versus standard care alone were $5277, $9980, $12,305, $16,705, and $23,227 per quality-adjusted life-year gained in Korea, Australia, Taiwan, Japan, and Singapore, respectively. When using add-on dapagliflozin to standard care versus standard care alone, ~ 100% of simulations were cost-effective at a willingness-to-pay threshold of one gross domestic product per capita of the given Asia–Pacific country; however, the probability of being cost-effective for using add-on dapagliflozin decreased when the time horizon for simulation was restricted to 18 months and when the cardiovascular mortality for the two treatments (43.8% and 33.0%, respectively) was assumed to be the same. The cost-effectiveness results were most sensitive to cardiovascular mortality of treatment. Conclusions Adding dapagliflozin to standard care is cost-effective for HFrEF in healthcare systems in the Asia–Pacific region, which supports the rational use of dapagliflozin for HFrEF in this region.

Objective: To comprehensively synthesise the evolution of health-economic evaluation models (HEEMs) of all OA interventions including preventions, core treatments, adjunct non-pharmacological interventions, pharmacological and surgical treatments. Methods: The literature was searched within health-economic/biomedical databases. Data extracted included: OA type, population characteristics, model setting/type/events, study perspective, comparators; and the reporting quality of the studies was assessed. The review protocol was registered at the International Prospective Register of Systematic Reviews (registration: CRD42018092937). Results: Eighty-eight studies were included. Pharmacological and surgical interventions were the focus in 51% and 44% studies, respectively. Twenty-four studies adopted a societal perspective (with increasing popularity after 2013), however most (63%) did not include indirect costs. Quality-adjusted life years (QALYs) was the most popular outcome measure since 2008. Markov models were used by 62% of studies, with increasing popularity since 2008. Until 2010, most studies used short-to-medium time horizons; subsequently a lifetime horizon became popular. Eighty-six percent of studies reported discount rate(s) (predominantly between 3% and 5%). Studies published after 2002 had a better coverage of OA-related adverse events (AEs). Reporting quality significantly improved after 2001. Conclusions: OA HEEMs have evolved and improved substantially over time, with focus shifting from short-to-medium-term pharmacological decision-tree models to surgical-focused lifetime Markov models. Indirect costs of OA are frequently not considered, despite using a societal perspective. There was lack of reporting sensitivity of model outcome to input parameters including discount rate, OA definition, and population parameters. Whilst the coverage of OA-related AEs has improved over time, it is still not comprehensive.

An important proportion of asthma patients remain uncontrolled despite the use of inhaled corticosteroids and long-acting beta-agonists. Some add-on therapies, like azithromycin, have been recommended for this subgroup of patients. The purpose of this study was to assess the cost-effectiveness of azithromycin as an add-on therapy to ICS + LABA for patients with severe asthma.A probabilistic Markov model was created to estimate the cost and quality-adjusted life-years (QALYs) of patients with severe asthma in Colombia. The total costs and QALYS of two interventions, including standard therapy (ICS + LABA), and add-on therapy with azithromycin, were calculated over a lifetime horizon. Multiple sensitivity analyses were conducted. Cost-effectiveness was evaluated at a willingness-to-pay value of $19,000.The model suggests a potential gain of 0.037 QALYs per patient per year on azithromycin, with a difference of US $718 in favor of azithromycin, showing dominance with respect to SOC. A position of dominance negates the need to calculate an incremental cost-effectiveness ratio. In the deterministic sensitivity analyses, our base-case results were robust to variations in all assumptions and parameters.Add-on therapy with azithromycin was found to be cost-effective when added to usual care in patients who remain uncontrolled despite treatment with medium or high-dose ICS/LABA.

BACKGROUND: Acute myocardial infarction (AMI) is a common cause of hospital admissions, readmissions, and mortality worldwide. Digital health interventions (DHIs) that promote self-management, adherence to guideline-directed therapy, and cardiovascular risk reduction may improve health outcomes in this population. The “Corrie” DHI consists of a smartphone application, smartwatch and wireless blood pressure monitor to support medication tracking, education, vital signs monitoring and care coordination. We aimed to assess the cost-effectiveness of this DHI plus standard care in reducing 30-day readmissions among AMI patients in comparison to standard care alone. METHODS: A Markov model was used to explore cost-effectiveness from the hospital perspective. The time horizon of the analysis was 1 year, with 30-day cycles, using inflation-adjusted cost data with no discount rate. Currencies were quantified in US dollars and effectiveness was measured in quality-adjusted life year (QALYs). The results were interpreted as an incremental cost-effectiveness ratio at a threshold of $100,000 per QALY. Univariate sensitivity and multivariate probabilistic sensitivity analyses tested model uncertainty. RESULTS: The DHI reduced costs and increased QALYs on average, dominating standard care in 99.7% of simulations in the probabilistic analysis. Based on the assumption that the DHI costs $2,750 per patient, use of the DHI leads to a cost-savings of $7,319 per patient compared to standard care alone. CONCLUSIONS: Our results demonstrate that this DHI is cost-saving through the reduction of risk for all-cause readmission following AMI. DHIs that promote improved adherence with guideline-based healthcare can result in reduced hospital readmissions. CLINICAL TRIAL REGISTRATION: NCT03760796; https://clinicaltrials.gov/ct2/show/NCT03760796

In this work, we predict the prevalence of type 2 diabetes among adult Rwandan people. We used the Metropolis-Hasting method that involved calculating the metropolis ratio. The data are those reported by World Health Organiation in 2015. Considering Suffering from diabetes, Overweight, Obesity, Dead and other subject as states of mathematical model, the transition matrix whose elements are probabilities is generated using Metropolis-Hasting sampling. The numerical results show that the prevalence of type 2 diabetes increases from 2.8% in 2015 to reach 12.65% in 2020 and to 22.59% in 2025. Therefore, this indicates the urgent need of prevention by Rwandan health decision makers who have to play their crucial role in encouraging for example physical activity, regular checkups and sensitization of the masses. Keywords: Non communicable diseases; type 2 diabetes; Markov Chain Monte Carlo method; Metropolis-Hasting method; Transition probabilities.rds

Background: Glycemic index (GI) measures postprandial blood sugar after consumption of carbohydrate-rich foodstuff. Kenya is yet to fully embrace this concept in prevention and management of diabetes mellitus. Objective: To review and tabulate GIs of locally consumed foods in order to improve dietary management of diabetes mellitus. Methodology: A literature search was conducted using Google scholar and PubMed databases which identified 7 articles on glycemic index values of Kenyan foods published between 2002 and 2020. Two articles failed to meet the inclusion criteria and five proceeded for review. Key search words used included GI, glycemic load and glycemic response combined with Kenya. The data was reported depending on whether the testing involved healthy individuals or patients suffering from diabetes mellitus. Results: Nine individual foods and 7 mixed meals were identified. Low GI foods included beans and whole maize ugali consumed alongside cowpea leaves. High GI foods included whole maize ugali eaten with beef, boiled rice, boiled cassava and cassava-sorghum ugali eaten with silver fish. Conclusion: Proper meal mixing is important in diabetes management. Cowpea leaves and beans possess GI lowering po- tential. This information can be used to improve guidance on food choices for diabetes patients. Keywords: Glycemic index; glycemic load and glycemic response; Kenya.

Background We conducted a cost-effectiveness analysis incorporating recent phase III clinical trial (MONALEESA-7) data to evaluate the cost-effectiveness of ribociclib (RIB) as a first-line treatment for premenopausal women with hormone receptor (HR)-positive and human epidermal growth factor receptor 2 (HER2)-negative advanced breast cancer (ABC) from the United States healthcare payer perspective. In addition, because RIB has not been marketed in China, we identified the range of drug costs for which RIB could be considered cost effective from a Chinese healthcare system perspective. Patients and Methods A Markov model was developed to evaluate the cost-effectiveness of adding RIB to endocrine therapy over a lifetime. The clinical outcomes and utility data were obtained from published literature. Costs data were obtained from United States and Chinese official websites, and we determined the potential price for RIB in China based on its price in the United States. The main outcomes of this study were the incremental cost-effectiveness ratio (ICER) and quality-adjusted life-years (QALYs). Results The model projected that mean outcome was better with RIB and endocrine combined (3.83366 QALYs) than with endocrine therapy alone (2.71203 QALYs). In the United States, RIB and endocrine therapy cost an additional $604,960.06, resulting in an ICER of $539,357.95/QALY compared with endocrine monotherapy. Subgroup analyses indicated that, in China, the projected mean outcomes were better for RIB and endocrine therapy (6.37 QALYs) than for endocrine monotherapy (2.71 QALYs). The corresponding incremental costs were $224,731.88943. Thus, the ICER comparing RIB and endocrine therapy with endocrine therapy alone represented a $61,454.96/QALY gain. Conclusion Additional use of RIB is estimated to not be cost effective as a first-line treatment for premenopausal women with HR-positive, HER2-negative ABC in the United States. A value-based price for the cost of RIB is less than $31.74/200 mg for China.

Objective To determine the cost effectiveness of pembrolizumab/lenvatinib (P/L) versus standard-of-care carboplatin/paclitaxel (C/T) as first-line systemic therapy for patients with advanced/recurrent endometrial cancer. Methods We designed a Markov model to simulate treatment outcomes for advanced/recurrent endometrial cancer patients whose tumors are either microsatellite stable (MSS) or have high microsatellite instability (MSI-high). We adopted a healthcare sector perspective for the analysis. Model inputs for costs, health utility, and clinical estimates were obtained from the literature including data from GOG0209 and KEYNOTE-146. Primary outcomes included costs of care, quality-adjusted life years (QALYs), and the incremental cost-effectiveness ratio (ICER). The time-horizon was three years and the discount rate was 3% annually. Results In a MSS cohort, compared to C/T, first-line treatment with P/L increased treatment costs by $212,670 and decreased QALYs by 0.28 per patient. In a MSI-high cohort, compared to C/T, P/L increased costs by $313,487 and increased QALYs by 0.11 per patient, representing an ICER of $2,849,882 per QALY. Sensitivity analyses found that the price of the new drugs was the most important determinant of the ICER and that the price of the new drugs would need to decrease by 85% to $2817 per cycle to reach a $150,000/QALY threshold. Conclusion In the MSS model, we found that first-line therapy for advanced or recurrent endometrial cancer with P/L increased costs and worsened outcomes compared to C/T. In the MSI-high model, P/L improved survival and QALYs compared to C/T but was not cost-effective at the current cost of the drugs.

Public health officials discouraged travel and non-household gatherings for Thanksgiving, but data suggests that travel increased over the holidays. The objective of this analysis was to assess associations between holiday gatherings and SARS-CoV-2 positivity in the weeks following Thanksgiving. Using an online survey, we sampled 7770 individuals across 10 US states from December 4–18, 2020, about 8–22 days post-Thanksgiving. Participants were asked about Thanksgiving, COVID-19 symptoms, and SARS-CoV-2 testing and positivity in the prior 2 weeks. Logistic regression was used to identify factors associated with SARS-CoV-2 positivity and COVID-19 symptoms in the weeks following Thanksgiving. An activity score measured the total number of non-essential activities an individual participated in the prior 2 weeks. The probability of community transmission was estimated using Markov Chain Monte Carlo (MCMC) methods. While 47.2% had Thanksgiving at home with household members, 26.9% had guests and 25.9% traveled. There was a statistically significant interaction between how people spent Thanksgiving, the frequency of activities, and SARS-CoV-2 test positivity in the prior 2 weeks (p one non-essential activity/day in the prior 2 weeks). Had individuals limited the number and frequency of activities post-Thanksgiving, cases in surveyed individuals would be reduced by > 50%. As travel continues to increase and the more contagious Delta variant starts to dominate transmission, it is critical to promote how to gather in a “low-risk” manner (e.g., minimize other non-essential activities) to mitigate the need for nationwide shelter-at-home orders.

The ability to predict an individual’s menstrual cycle length to a high degree of precision could help female athletes to track their period and tailor their training and nutrition correspondingly. Such individualisation is possible and necessary, given the known inter-individual variation in cycle length. To achieve this, a hybrid predictive model was built using data on 16,524 cycles collected from a sample of 2125 women (mean age 34.38 years, range 18.00–47.10, number of menstrual cycles ranging from 4 to 53). A mixed-effect state-space model was fitted to capture the within-subject temporal correlation, incorporating a Bayesian approach for process forecasting to predict the duration (in days) of the next menstrual cycle. The modelling procedure was split into three steps (1) a time trend component using a random walk with an overdispersion parameter, (2) an autocorrelation component using an autoregressive moving-average model, and (3) a linear predictor to account for covariates (e.g. injury, stomach cramps, training intensity). The inclusion of an overdispersion parameter suggested that $$26.36\%$$ 26.36 % $$[23.68\%,29.17\%]$$ [ 23.68 % , 29.17 % ] of cycles in the sample were overdispersed. The random walk standard deviation for a non-overdispersed cycle is $$27.41 \pm 1.05$$ 27.41 ± 1.05 [1.00, 1.09] days while under an overdispersed cycle, the menstrual cycle variance increase in 4.78 [4.57, 5.00] days. To assess the performance and prediction accuracy of the model, each woman’s last observation was used as test data. The root mean square error (RMSE), concordance correlation coefficient and Pearson correlation coefficient (r) between the observed and predicted values were calculated. The model had an RMSE of 1.6412 days, a precision of 0.7361 and overall accuracy of 0.9871. In conclusion, the hybrid model presented here is a helpful approach for predicting menstrual cycle length, which in turn can be used to support female athlete wellness.

Corona Virus Disease 2019 (COVID-19) has spread rapidly to countries all around the world from the end of 2019, which caused a great impact on global health and has had a huge impact on many countries. Since there is still no effective treatment, it is essential to making effective predictions for relevant departments to make responses and arrangements in advance. Under the limited data, the prediction error of LSTM model will increase over time, and its prone to big bias for medium- and long-term prediction. To overcome this problem, our study proposed a LSTM-Markov model, which uses Markov model to reduce the prediction error of LSTM model. Based on confirmed case data in the US, Britain, Brazil and Russia, we calculated the training errors of LSTM and constructed the probability transfer matrix of the Markov model by the errors. And finally, the prediction results were obtained by combining the output data of LSTM model with the prediction errors of Markov Model. The results show that: compared with the prediction results of the classical LSTM model, the average prediction error of LSTM-Markov is reduced by more than 75%, and the RMSE is reduced by more than 60%, the mean $${R}^{2}$$ R 2 of LSTM-Markov is over 0.96. All those indicators demonstrate that the prediction accuracy of proposed LSTM-Markov model is higher than that of the LSTM model to reach more accurate prediction of COVID-19.

INTRODUCTION: Neoadjuvant therapy (NAT) is an emerging strategy for operable pancreatic ductal adenocarcinoma (PDAC). While neoadjuvant therapy increases multimodal therapy completion, it risks functional decline and treatment drop out. We used decision analysis to determine optimal management of localized PDAC and consider risks faced by elderly patients. METHODS: A Markov cohort decision analysis model evaluated treatment options for a 60-year-old patient with resectable PDAC: 1) upfront pancreaticoduodenectomy or 2) neoadjuvant therapy (NAT). One-way and probabilistic sensitivity analyses were performed. A sub-analysis considered the scenario of a 75-year-old patient. RESULTS: For the base case, NAT offered an incremental survival gain of 4.6 months compared to SF (overall survival: 26.3 vs 21.7 months). In One-way sensitivity analyses, findings were sensitive to recurrence free survival for NAT patients undergoing adjuvant, probability of completing NAT, and probability of being resectable at exploration after NAT. On probabilistic analysis, NAT was favored in a majority of trials (97%) with a median survival benefit of 5.1 months. In altering the base case for the 75-year-old scenario, NAT had a survival benefit of 3.8 months. CONCLUSIONS: This analysis demonstrates a significant benefit to neoadjuvant therapy in patients with localized PDAC. This benefit persists even in the elderly cohort.

To the best of our knowledge there have been no randomized controlled trials comparing lobectomy—a standard treatment for patients with early-stage non-small cell lung cancer (NSCLC)—and particle beam therapy (PBT), the best performing existing radiotherapy. We conducted a virtual randomized trial in medically operable patients with stage IA NSCLC to compare lobectomy and PBT effectiveness. A Markov model was developed to predict life expectancy after lobectomy and PBT in a cohort of patients with stage IA NSCLC. Ten thousand virtual patients were randomly assigned to each group. Sensitivity analyses were performed as model variables and scenarios changed to determine which treatment strategy was best for improving life expectancy. All estimated model parameters were determined using variables extracted from a systematic literature review of previously published articles. The preferred strategy differed depending on patient age. In young patients, lobectomy showed better life expectancy than that of PBT. The difference in life expectancy between lobectomy and PBT was statistically insignificant in older patients. Our model predicted lobectomy as the preferred strategy when operative mortality was under 5%. However, the preferred strategy changed to PBT if operative mortality post lobectomy was over 5%. For medically operable patients with stage IA NSCLC, our Markov model revealed the preferred strategy of lobectomy or PBT regarding operative mortality changed with varying age and comorbidity. Until randomized controlled trial results become available, we hope the current results will provide a rationale background for clinicians to decide treatment modalities for patients with stage IA NSCLC.

IntroductionWorld Health Organization recommends rotavirus vaccine for all national immunization programs (NIPs). To provide country-specific evidence, we conducted economic evaluation of a monovalent rotavirus vaccination using specific data of the pilot phase in Thailand.MethodA Markov model was adopted to compare the 2020 birth cohort once receiving rotavirus vaccination versus no vaccination from healthcare and societal perspective over five years. Data on disease burden, vaccine effectiveness, costs, and utilities were taken from a cohort study in two provinces of Thailand. Sensitivity analyses were performed to test the robustness of the results.ResultsRotavirus vaccination would reduce rotavirus diarrhea and costs of illness by 48% and 71%, respectively, over the first five years of life. At USD 13 per dose, vaccine was cost-effective with the ICERs of USD 4,114 and USD 1,571per QALY gained from healthcare and societal perspective, respectively. Results were sensitive to incidence and vaccine cost. The budget for vaccine purchasing was estimated at USD13 million per year.ConclusionIncorporating rotavirus vaccination into the NIP substantially reduced health and cost outcomes and was cost-effective for both perspectives. However, the government needs to negotiate vaccine price prior to program implementation to achieve favorable budget impact.

The clinical effects of remimazolam (an investigational, ultra‐short acting benzodiazepine being studied in procedural sedation) were measured using the Modified Observer’s Assessment of Awareness/Sedation Scale (MOAA/S). The objective of this analysis was to develop a population pharmacokinetic/pharmacodynamic model to describe remimazolam‐induced sedation with fentanyl over time in procedural sedation. MOAA/S from 10 clinical phase I–III trials were pooled for analysis, where data were collected after administration of placebo or remimazolam with or without concomitant fentanyl. A Markov model described transition states for 35,356 MOAA/S‐time observations from 1071 subjects. Effect‐compartment models of remimazolam and fentanyl linked plasma concentrations to the Markov model, and drug effects were described using a synergistic maximum effect (Emax) model. Simulations were performed to identify the optimal remimazolam‐fentanyl combination doses in procedural sedation. Fentanyl showed synergistic effects with remimazolam in sedation. Increasing age was related to longer recovery from sedation. Patients with body mass index greater than 25 kg/m2 had ~30% higher rates of distribution from plasma to the effect site (keo), indicating a slightly faster onset of sedation. Simulations showed that remimazolam 5 mg was more appropriate than 4 or 6 mg when administered with fentanyl 50 μg. The model and simulations support that a combination of remimazolam 5 mg with fentanyl 50 μg is an appropriate dosing regimen and the dose of remimazolam does not need to be changed in elderly patients, but some elderly patients may have a longer duration of sedation.

BackgroundRecovery in schizophrenia is a complex process, involving clinical, societal and personal recovery. Until now, studies analysed these domains separately, without examining their mutual relations and changes over time.AimsThis study aimed to examine different states of recovery and transition rates between states.MethodThe Pharmacotherapy Monitoring and Outcome Survey (2006–2017) yearly assesses patients with schizophrenia in the Northern Netherlands. Data from 2327 patients with one up to 11 yearly measurements on clinical, societal and personal recovery were jointly analysed with a mixture latent Markov model (MLMM).ResultsThe selected MLMM had four states that differed in degree and pattern of recovery outcomes. Patients in state 1 were least recovered on any domain (16% of measurements), and partly recovered in states 2 (25%; featured by negative symptoms) and 3 (21%; featured by positive symptoms). Patients in state 4 (38%) were most recovered, except for work, study and housekeeping. At the subsequent measurement, the probability of remaining in the same state was 77–89%, transitioning to a better state was 4–12% and transitioning to a worse state was 4–6%; no transitions occurred between states 1 and 4. Female gender, shorter illness duration and less schizophrenia were more prevalent in better states.ConclusionsQuite a high recovery rate was present among a substantial part of the measurements (38%, state 4), with a high probability (89%) of remaining in this state. Transition rates in the other states might increase to a more favourable state by focusing on adequate treatment of negative and positive symptoms and societal problems.

The efficacy of quantitative ultrasound (QUS) multi-parametric imaging in conjunction with unsupervised classification algorithms was investigated for the first time in characterizing intra-tumor regions to predict breast tumor response to chemotherapy before the start of treatment. QUS multi-parametric images of breast tumors were generated using the ultrasound radiofrequency data acquired from 181 patients diagnosed with locally advanced breast cancer and planned for neo-adjuvant chemotherapy followed by surgery. A hidden Markov random field (HMRF) expectation maximization (EM) algorithm was applied to identify distinct intra-tumor regions on QUS multi-parametric images. Several features were extracted from the segmented intra-tumor regions and tumor margin on different parametric images. A multi-step feature selection procedure was applied to construct a QUS biomarker consisting of four features for response prediction. Evaluation results on an independent test set indicated that the developed biomarker coupled with a decision tree model with adaptive boosting (AdaBoost) as the classifier could predict the treatment response of patient at pre-treatment with an accuracy of 85.4% and an area under the receiver operating characteristic (ROC) curve (AUC) of 0.89. In comparison, the biomarkers consisted of the features derived from the entire tumor core (without consideration of the intra-tumor regions), and the entire tumor core and the tumor margin could predict the treatment response of patients with an accuracy of 74.5% and 76.4%, and an AUC of 0.79 and 0.76, respectively. Standard clinical features could predict the therapy response with an accuracy of 69.1% and an AUC of 0.6. Long-term survival analyses indicated that the patients predicted by the developed model as responders had a significantly better survival compared to the non-responders. Similar findings were observed for the two response cohorts identified at post-treatment based on standard clinical and pathological criteria. The results obtained in this study demonstrated the potential of QUS multi-parametric imaging integrated with unsupervised learning methods in identifying distinct intra-tumor regions in breast cancer to characterize its responsiveness to chemotherapy prior to the start of treatment.

Background Malaria patients can have two or more haplotypes in their blood sample making it challenging to identify which haplotypes they carry. In addition, there are challenges in measuring the type and frequency of resistant haplotypes in populations. This study presents a novel statistical method Gibbs sampler algorithm to investigate this issue. Results The performance of the algorithm is evaluated on simulated datasets consisting of patient blood samples characterized by their multiplicity of infection (MOI) and malaria genotype. The simulation used different resistance allele frequencies (RAF) at each Single Nucleotide Polymorphisms (SNPs) and different limit of detection (LoD) of the SNPs and the MOI. The Gibbs sampler algorithm presents higher accuracy among high LoD of the SNPs or the MOI, validated, and deals with missing MOI compared to previous related statistical approaches. Conclusions The Gibbs sampler algorithm provided robust results when faced with genotyping errors caused by LoDs and functioned well even in the absence of MOI data on individual patients.

To evaluate the cost-effectiveness of an artificial intelligence electrocardiogram (AI-ECG) algorithm under various clinical and cost scenarios when used for universal screening at age 65.We used decision analytic modeling to perform a cost-effectiveness analysis of the use of AI-ECG to screen for asymptomatic left ventricular dysfunction (ALVD) once at age 65 compared with no screening. This screening consisted of an initial screening decision tree and subsequent construction of a Markov model. One-way sensitivity analysis on various disease and cost parameters to evaluate cost-effectiveness at both $50,000 per quality-adjusted life year (QALY) and $100,000 per QALY willingness-to-pay threshold.We found that for universal screening at age 65, the novel AI-ECG algorithm would cost $43,351 per QALY gained, test performance, disease characteristics, and testing cost parameters significantly affect cost-effectiveness, and screening at ages 55 and 75 would cost $48,649 and $52,072 per QALY gained, respectively. Overall, under most of the clinical scenarios modeled, coupled with its robust test performance in both testing and validation cohorts, screening with the novel AI-ECG algorithm appears to be cost-effective at a willingness-to-pay threshold of $50,000.Universal screening for ALVD with the novel AI-ECG appears to be cost-effective under most clinical scenarios with a cost of$50,000 per QALY. Cost-effectiveness is particularly sensitive to both the probability of disease progression and the cost of screening and downstream testing. To improve cost-effectiveness modeling, further study of the natural progression and treatment of ALVD and external validation of AI-ECG should be undertaken.

This study aimed to evaluate the patterns of changes in obesity indices over time in prediabetic subjects and to classify these subjects as either having a low, moderate, and high risk for developing diabetes in the future. This study was conducted among 1228 prediabetics. The patterns of changes in obesity indices based on three measurements including first, mean values during the follow-up period, and last visit from these indices were evaluated by using the latent Markov model (LMM). The mean (standard deviation) age of subjects was 44.0 (6.8) years and 73.6% of them were female. LMM identified three latent states of subjects in terms of change in all anthropometric indices: a low, moderate, and high tendency to progress diabetes with the state sizes (29%, 45%, and 26%), respectively. LMM showed that the probability of transitioning from a low to a moderate tendency to progress diabetes was higher than the other transition probabilities. Based on a long-term evaluation of patterns of changes in obesity indices, our results reemphasized the values of all five obesity indices in clinical settings for identifying high-risk prediabetic subjects for developing diabetes in future and the need for more effective obesity prevention strategies.

Objectives In breast cancer screening, two readers separately examine each woman’s mammograms for signs of cancer. We examined whether preventing the two readers from seeing each other’s decisions (blinding) affects behaviour and outcomes. Methods This cohort study used data from the CO-OPS breast-screening trial (1,119,191 women from 43 screening centres in England) where all discrepant readings were arbitrated. Multilevel models were fitted using Markov chain Monte Carlo to measure whether reader 2 conformed to the decisions of reader 1 when they were not blinded, and the effect of blinding on overall rates of recall for further tests and cancer detection. Differences in positive predictive value (PPV) were assessed using Pearson’s chi-squared test. Results When reader 1 recalls, the probability of reader 2 also recalling was higher when not blinded than when blinded, suggesting readers may be influenced by the other’s decision. Overall, women were less likely to be recalled when reader 2 was blinded (OR 0.923; 95% credible interval 0.864, 0.986), with no clear pattern in cancer detection rate (OR 1.029; 95% credible interval 0.970, 1.089; Bayesian p value 0.832). PPV was 22.1% for blinded versus 20.6% for not blinded (p < 0.001). Conclusions Our results suggest that when not blinded, reader 2 is influenced by reader 1’s decisions to recall (alliterative bias) which would result in bypassing arbitration and negate some of the benefits of double-reading. We found a relationship between blinding the second reader and slightly higher PPV of breast cancer screening, although this analysis may be confounded by other centre characteristics. Key Points • In Europe, it is recommended that breast screening mammograms are analysed by two readers but there is little evidence on the effect of ‘blinding’ the readers so they cannot see each other’s decisions. • We found evidence that when the second reader is not blinded, they are more likely to agree with a recall decision from the first reader and less likely to make an independent judgement (alliterative error). This may reduce overall accuracy through bypassing arbitration. • This observational study suggests an association between blinding the second reader and higher positive predictive value of screening, but this may be confounded by centre characteristics.

Aim: To evaluate the cost–effectiveness of ribociclib plus fulvestrant versus fulvestrant in hormone receptor-positive/human EGF receptor 2-negative advanced breast cancer. Materials & methods: A three-state Markov model was developed to evaluate the costs and effectiveness over 10 years. Direct costs and utility values were obtained from previously published studies. We calculated incremental cost–effectiveness ratio to evaluate the cost–effectiveness at a willingness-to-pay threshold of $150,000 per additional quality-adjusted life year. Results: The incremental cost–effectiveness ratio was $1,073,526 per quality-adjusted life year of ribociclib plus fulvestrant versus fulvestrant. Conclusions: Ribociclib plus fulvestrant is not cost-effective versus fulvestrant in the treatment of advanced hormone receptor-positive/human EGF receptor 2-negative breast cancer. When ribociclib is at 10% of the full price, ribociclib plus fulvestrant could be cost-effective.

INTRODUCTION: Minimally invasive tests for Barrett's esophagus (BE) detection have raised the prospect of broader nonreflux-based testing. Cost-effectiveness studies have largely studied men aged 50 years with chronic gastroesophageal reflux disease (GERD) symptoms. We evaluated the comparative cost effectiveness of BE screening tests in GERD-based and GERD-independent testing scenarios. METHODS: Markov modeling was performed in 3 scenarios in 50 years old individuals: (i) White men with chronic GERD (GERD-based); (ii) GERD-independent (all races, men and women), BE prevalence 1.6%; and (iii) GERD-independent, BE prevalence 5%. The simulation compared multiple screening strategies with no screening: sedated endoscopy (sEGD), transnasal endoscopy, swallowable esophageal cell collection devices with biomarkers, and exhaled volatile organic compounds. A hypothetical cohort of 500,000 individuals followed for 40 years using a willingness to pay threshold of $100,000 per quality-adjusted life year (QALY) was simulated. Incremental cost-effectiveness ratios (ICERs) comparing each strategy with no screening and comparing screening strategies with each other were calculated. RESULTS: In both GERD-independent scenarios, most non-sEGD BE screening tests were cost effective. Swallowable esophageal cell collection devices with biomarkers were cost effective (

OBJECTIVES: Smoking is a leading cause of death worldwide. Cessation aids include varenicline, bupropion, nicotine replacement therapy (NRT), and e-cigarettes at various doses (low, standard and high) and used alone or in combination with each other. Previous cost-effectiveness analyses have not fully accounted for adverse effects nor compared all cessation aids. The objective was to determine the relative cost-effectiveness of cessation aids in the United Kingdom.METHODS: An established Markov cohort model was adapted to incorporate health outcomes and costs due to depression and self-harm associated with cessation aids, alongside other health events. Relative efficacy in terms of abstinence and major adverse neuropsychiatric events was informed by a systematic review and network meta-analysis. Base case results are reported for UK-licensed interventions only. Two sensitivity analyses are reported, one including unlicensed interventions and another comparing all cessation aids but removing the impact of depression and self-harm. The sensitivity of conclusions to model inputs was assessed by calculating the expected value of partial perfect information.RESULTS: When limited to UK-licensed interventions, varenicline standard-dose and NRT standard-dose were most cost-effective. Including unlicensed interventions, e-cigarette low-dose appeared most cost-effective followed by varenicline standard-dose + bupropion standard-dose combined. When the impact of depression and self-harm was excluded, varenicline standard-dose + NRT standard-dose was most cost-effective, followed by varenicline low-dose + NRT standard-dose.CONCLUSION: Although found to be most cost-effective, combined therapy is currently unlicensed in the United Kingdom and the safety of e-cigarettes remains uncertain. The value-of-information analysis suggested researchers should continue to investigate the long-term effectiveness and safety outcomes of e-cigarettes in studies with active comparators.

Advanced single-cell profiling technologies promote exploration of cell heterogeneity, and clustering of single-cell RNA (scRNA-seq) data enables discovery of coexpression genes and network relationships between genes. In particular, single-cell profiling of circulating tumor cells (CTCs) can provide unique insights into tumor heterogeneity (including in triple-negative breast cancer (TNBC)), while scRNA-seq leads to better understanding of subclonal architecture and biological function. Despite numerous reports suggesting a direct correlation between circulating tumor cells (CTCs) and poor clinical outcomes, few studies have provided a thorough heterogeneity characterization of CTCs. In addition, TNBC is a disease with not only intertumor but also intratumor heterogeneity and represents various biological distinct subgroups that may have relationships with immune functions that are not clearly established yet. In this article, we introduce a new scheme for detecting genotypic characterization of single-cell heterogeneities and apply it to CTC and TNBC single-cell RNA-seq data. First, we use an existing mixture exponential family graph model to partition the cell-cell network; then, with the Markov random field model, we obtain more flexible network rewiring. Finally, we find the cell heterogeneity and network relationships according to different high coexpression gene modules in different cell subsets. Our results demonstrate that this scheme provides a reasonable and effective way to model different cell clusters and different biological enrichment gene clusters. Thus, using different internal coexpression genes of different cell clusters, we can infer the differences in tumor composition and diversity.

Screening tests are widely recommended for the early detection of disease among asymptomatic individuals. While detecting disease at an earlier stage has the potential to improve outcomes, screening also has negative consequences, including false positive results which may lead to anxiety, unnecessary diagnostic procedures, and increased healthcare costs. In addition, multiple false positive results could discourage participating in subsequent screening rounds. Screening guidelines typically recommend repeated screening over a period of many years, but little prior research has investigated how often individuals receive multiple false positive test results. Estimating the cumulative risk of multiple false positive results over the course of multiple rounds of screening is challenging due to the presence of censoring and competing risks, which may depend on the false positive risk, screening round, and number of prior false positive results. To address the general challenge of estimating the cumulative risk of multiple false positive test results, we propose a nonhomogeneous multistate model to describe the screening process including competing events. We developed alternative approaches for estimating the cumulative risk of multiple false positive results using this multistate model based on existing estimators for the cumulative risk of a single false positive. We compared the performance of the newly proposed models through simulation studies and illustrate model performance using data on screening mammography from the Breast Cancer Surveillance Consortium. Across most simulation scenarios, the multistate extension of a censoring bias model demonstrated lower bias compared to other approaches. In the context of screening mammography, we found that the cumulative risk of multiple false positive results is high. For instance, based on the censoring bias model, for a high-risk individual, the cumulative probability of at least two false positive mammography results after 10 rounds of annual screening is 40.4.

Background The COVID-19 outbreak in Wuhan started in December 2019 and was under control by the end of March 2020 with a total of 50,006 confirmed cases by the implementation of a series of nonpharmaceutical interventions (NPIs) including unprecedented lockdown of the city. This study analyzes the complete outbreak data from Wuhan, assesses the impact of these public health interventions, and estimates the asymptomatic, undetected and total cases for the COVID-19 outbreak in Wuhan. Methods By taking different stages of the outbreak into account, we developed a time-dependent compartmental model to describe the dynamics of disease transmission and case detection and reporting. Model coefficients were parameterized by using the reported cases and following key events and escalated control strategies. Then the model was used to calibrate the complete outbreak data by using the Monte Carlo Markov Chain (MCMC) method. Finally we used the model to estimate asymptomatic and undetected cases and approximate the overall antibody prevalence level. Results We found that the transmission rate between Jan 24 and Feb 1, 2020, was twice as large as that before the lockdown on Jan 23 and 67.6% (95% CI [0.584,0.759]) of detectable infections occurred during this period. Based on the reported estimates that around 20% of infections were asymptomatic and their transmission ability was about 70% of symptomatic ones, we estimated that there were about 14,448 asymptomatic and undetected cases (95% CI [12,364,23,254]), which yields an estimate of a total of 64,454 infected cases (95% CI [62,370,73,260]), and the overall antibody prevalence level in the population of Wuhan was 0.745% (95% CI [0.693%,0.814%]) by March 31, 2020. Conclusions We conclude that the control of the COVID-19 outbreak in Wuhan was achieved via the enforcement of a combination of multiple NPIs: the lockdown on Jan 23, the stay-at-home order on Feb 2, the massive isolation of all symptomatic individuals via newly constructed special shelter hospitals on Feb 6, and the large scale screening process on Feb 18. Our results indicate that the population in Wuhan is far away from establishing herd immunity and provide insights for other affected countries and regions in designing control strategies and planing vaccination programs.

Objective To estimate the cost-effectiveness of multitarget stool DNA testing (MT-sDNA) compared with colonoscopy and fecal immunochemical testing (FIT) for Alaska Native adults. Patients and Methods A Markov model was used to evaluate the 3 screening test effects over 40 years. Outcomes included colorectal cancer (CRC) incidence and mortality, costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios (ICERs). The study incorporated updated evidence on screening test performance and adherence and was conducted from December 15, 2016, through November 6, 2019. Results With perfect adherence, CRC incidence was reduced by 52% (95% CI, 46% to 56%) using colonoscopy, 61% (95% CI, 57% to 64%) using annual FIT, and 66% (95% CI, 63% to 68%) using MT-sDNA. Compared with no screening, perfect adherence screening extends life by 0.15, 0.17, and 0.19 QALYs per person with colonoscopy, FIT, and MT-sDNA, respectively. Colonoscopy is the most expensive strategy: approximately $110 million more than MT-sDNA and $127 million more than FIT. With imperfect adherence (best case), MT-sDNA resulted in 0.12 QALYs per person vs 0.05 and 0.06 QALYs per person by FIT and colonoscopy, respectively. Probabilistic sensitivity analyses supported the base-case analysis. Under varied adherence scenarios, MT-sDNA either dominates or is cost-effective (ICERs, $1740-$75,868 per QALY saved) compared with FIT and colonoscopy. Conclusion Each strategy reduced costs and increased QALYs compared with no screening. Screening by MT-sDNA results in the largest QALY savings. In Markov model analysis, screening by MT-sDNA in the Alaska Native population was cost-effective compared with screening by colonoscopy and FIT for a wide range of adherence scenarios.

Background A major challenge in clinical research is population heterogeneity and we need to consider both historical response and current condition of an individual in considering medical decision making. The idea of precise medicine cannot be fully accounted for in traditional randomized controlled trials. Reinforcement learning (RL) is developing rapidly and has found its way into various fields including clinical medicine in which RL is employed to find an optimal treatment strategy. The key idea of RL is to optimize the treatment policy depending on the current state and previous treatment history, which is consistent with the idea behind dynamic programming (DP). DP is a prototype of RL and can be implemented when the system dynamics can be fully quantified. Methods The present article aims to illustrate how to perform DP algorithm in a clinical scenario of Sepsis resuscitation. The state transition dynamics are constructed in the framework of Markov Decision Process. The state space is defined by mean arterial pressure (MAP) and lactate; the action space is comprised of fluid administration and vasopressor. The implementation of policy evaluation, policy improvement and iteration are explained with R code. Results The DP algorithm was able to find the optimal treatment policy depending on the current states and previous conditions. The iteration process converged at finite steps. We defined several functions such as nextStep(), policyEval() and policy_iteration() to implement the DP algorithm. Conclusions This article illustrates how DP can be used to solve a clinical problem. We show that DP is a potential useful tool to tailor treatment strategy to patients with different conditions/states. Potential audience of the paper are those who are interested in using DP for solving clinical problems with dynamic changing states.

Objective: To evaluate the long-term cost-effectiveness of ginkgolide plus aspirin compared with placebo plus aspirin treatment of ischemic stroke. Background: Stroke is the leading cause of death and long-term disability in China, with high incidence, high mortality, and heavy disease burden. In addition to Western medicines, Chinese clinical guidelines for diagnosis and treatment of acute ischemic stroke recommend application of Chinese patent medicines. Ginkgolide injection is commonly used in the clinical treatment of stroke in China to promote blood circulation and remove blood stasis. The economy of ginkgolide injection needs to be evaluated. Methods: A Markov model was constructed consisting of four disease states: no significant disability, disability, stroke recurrence, and death. Therapeutic data were taken from the Ginkgolide in Ischemic Stroke Patients with Large Artery Atherosclerosis (GISAA) study. Utilities and transition probabilities were extracted from the literature. Cost data were obtained from the China Health Statistics Yearbook and hospital record survey. Expected costs and quality-adjusted life-years (QALYs) of 13 years of cycles (calculated by average age of subjects and Chinese life expectancy) were calculated through TreeAge Pro11 software. The willingness-to-pay (WTP) threshold was set as the Chinese per capita Gross Domestic Product (GDP) in 2019, CN¥70,892/QALY. The results were analyzed by single factor and probability sensitivity analyses. Results: Ginkgolide plus aspirin had a higher expected per-patient cost than placebo plus aspirin but a higher QALYs. Compared with placebo plus aspirin, ginkgolide plus aspirin produced an incremental cost-effectiveness ratio of CN¥14,866.06/QALY, which is below the WTP threshold. Probabilistic sensitivity analysis suggested the acceptability of ginkgolide plus aspirin was higher than that of placebo plus aspirin. Conclusions: The present cost-effectiveness analysis showed that addition of ginkgolides to conventional treatment is cost-effective at a threshold the Chinese per capita GDP.