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Statistical bias correction (BC) is a widely used tool to post-process climate model biases in heat-stress impact studies, which are often based on the indices calculated from multiple dependent variables. This study compares four BC methods (three univariate and one multivariate) with two correction strategies (direct and indirect) for adjusting two heat-stress indices with different dependencies on temperature and relative humidity using multiple regional climate model simulations over South Korea. It would be helpful for reducing the ambiguity involved in the practical application of BC for climate modeling and end-user communities. Our results demonstrate that the multivariate approach can improve the corrected inter-variable dependence, which benefits the indirect correction of heat-stress indices depending on the adjustment of individual components, especially those indices relying equally on multiple drivers. On the other hand, the direct correction of multivariate indices using the quantile delta mapping univariate approach can also produce a comparable performance in the corrected heat-stress indices. However, our results also indicate that attention should be paid to the non-stationarity of bias brought by climate sensitivity in the modeled data, which may affect the bias-corrected results unsystematically. Careful interpretation of the correction process is required for an accurate heat-stress impact assessment.

PURPOSE The combination of oxaliplatin and fluoropyrimidine for 6 months is one of the standard options for adjuvant therapy for high-risk stage II and III colorectal cancers (CRCs). The optimal duration of oxaliplatin to diminish neurotoxicity without compromising efficacy needs to be clarified. PATIENTS AND METHODS This open-label, randomized, phase III, noninferiority trial randomly assigned patients with high-risk stage II and III CRC to 3 and 6 months of oxaliplatin with 6 months of fluoropyrimidine groups (3- and 6-month arms, respectively). The primary end point was disease-free survival (DFS), and the noninferiority margin was a hazard ratio (HR) of 1.25. RESULTS In total, 1,788 patients were randomly assigned to the 6-month (n = 895) and 3-month (n = 893) arms, and 83.6% in the 6-month arm and 85.7% in the 3-month arm completed the treatment. The neuropathy rates with any grade were higher in the 6-month arm than in the 3-month arm (69.5% v 58.3%; P < .0001). The 3-year DFS rates were 83.7% and 84.7% in the 6-month and 3-month arms, respectively, with an HR of 0.953 (95% CI, 0.769 to 1.180; test for noninferiority, P = .0065) within the noninferiority margin. Among patients with stage III CRC treated by capecitabine plus oxaliplatin, the 3-year DFS of the 3-month arm was noninferior as compared with that of the 6-month arm with an HR of 0.713 (95% CI, 0.530 to 0.959; P = .0009). However, among patients with high-risk stage II and stage III CRC treated by infusional fluorouracil, leucovorin, and oxaliplatin, the noninferiority of the 3-month arm compared with the 6-month arm was not proven. CONCLUSION This study suggests that adding 3 months of oxaliplatin to 6 months of capecitabine could be considered an alternative adjuvant treatment for stage III CRC (ClinicalTrials.gov identifier: NCT01092481 ).

Changes in summer heat extremes have been recorded all over the globe in recent years. East Asia is one of the most vulnerable areas for climate change, owing to a combination of natural and anthropogenic factors. The human experience of heat, however, does not only depend on the temperature itself but rather the combination of factors that regulate the exchange of heat with the environment. The present study uses Net Effective Temperature (NET), an index that combines the effects of temperature, humidity, and wind, to assess heat stress perception and its potential changes by the end of the century over East Asia. The data used in the study are maximums calculated from the three-hourly output of the 10 Coupled General Circulation Model (CGCM) - Regional Climate Model (CGM) chains participating in the Coordinated Regional Climate Downscaling Experiment (CORDEX)-East Asia phase 2. As human beings can acclimate to their environment, not only maximum values but also 95th percentiles of maximum values have been used. The assessment of the models showed that all of the models reproduced the current climate reasonably. The present study utilized two different scenarios, RCP8-5, and SSP5-8.5. In both scenarios, the increase in averages and 95th percentiles of both maximum temperatures and NETs over the whole domain has been projected. The increase in NET was projected to be higher than the increase in temperature itself, and the increase in the SSP5-8.5 scenario was projected to be higher than the increase in the RCP8.5 scenario, but the details of the warming patterns were dependent on the choice of model. Additionally, the Korean Peninsula and Japan have been shown to have the largest difference in the increase between heat stress and temperature, while the highest overall increase of both temperature and NET was projected over the North-Western part of the domain in both scenarios.

Tropical cyclones (TCs), which often form over the western North Pacific (WNP), have a large socioeconomic impact and result in destructive damages in East Asian countries. Therefore, it is critical to estimate future changes in TCs characteristics under the global warming. In this study, future characteristics of TCs using five regional climate models (RCMs) (i.g., RegCM4, GRIMs, WRF, CCLM, and HadGEM3-RA) were investigated in Coordinated Regional Climate Downscaling Experiment (CORDEX) East Asia domain. Five RCMs were forced by the UK Earth System Model (UKESM) under the historical and two Shared Socioeconomic Pathways (SSP) scenarios (SSP1-2.6 and SSP5-8.5). The simulation experiments were conducted at about 25-km horizontal resolution. The multi-RCM ensemble mean was used for analysis to reduce the uncertainty of a single RCM. In the historical period (1985-2014) during the TC season (June-November), the ensembled RCMs properly reproduced the TC genesis over the WNP comparable to the best track data. In the future climate, the RCMs tended to migrate the core region of TCs genesis more northward compared in the present climate. This migration could be related to weakening of vertical wind shear over the mid-latitudes, due to decreased meridional sea surface temperature gradient.

In the mid-latitudes, synoptic-scale phenomena like high and low-pressure systems generate the variability of the regional-scale weather system. To identify the weather variability of extra-tropical region storm track activity has been analyzed based on observations since the mid-nineteenth century. After early-stage research that directly counted the movement of cyclones, the time filtering method based on grid analysis has been used for an isolated disturbance with periods of 2~7 days. This bandpass filtering method has the advantage of being able to examine the distribution and the variability of the storm track spatially in vertical and horizontal space.In this study, we confirm the storm track activity in the East Asia region using the dynamical down-scale results from CORDEX (COordinated Regional climate Downscaling EXperiment) East Asia projects. We verify the reproducibility and confirm the temporal change in the storm track activity from various RCM data. In addition to the historical period, we examine the difference in storm track intensity over future climate change scenarios. Through this, we also discuss the role of added value from RCM. This work was funded by the Korea Meteorological Administration Research and Development Program under Grant KMI2022-01210.

Studies have shown that regional climate models (RCMs) can simulate local climates at a higher resolution for specific regions compared to global climate models (GCMs), making dynamic downscaling using RCMs a more effective approach. Therefore, RCMs have become valuable tools for evaluating the potential impacts of climate change on specific regions and for informing local adaptation strategies. To fully understand the added value (AV) of RCMs, it is essential to understand how the characteristics differ between land and ocean. The complex topography of East Asia, including land and sea, makes it a suitable region for evaluating the AV of RCMs. In this study, we compared two regional simulations that integrated the same RCMs but employed different GCMs from the Coordinated Regional Climate Downscaling Experiment for their ability to simulate storm tracks in East Asia. The results of the RCMs over a historical period were compared with their host Coupled Model Intercomparison Project GCM projections and high-resolution reanalysis. In mountainous regions, the AV of the RCMs weakened the bias of the GCM and improved its agreement with the reanalysis. In plains and coastal areas, owing to the increase in horizontal resolution in RCMs, small-scale phenomena are well represented, and the storm track of RCMs shows similar values to that of the GCM in maritime regions. This study demonstrates the value of RCMs for improving the accuracy of climate projections in East Asia, informing adaptation strategies, and enhancing climate research.

The quantitative assessment of the uncertainty components of future climate projections is critical for decision-makers and organizations to establish climate change adaptation and mitigation strategies at regional or local scales. This is the first study in which the changes in the uncertainty components of future temperature and precipitation projections are quantitatively evaluated using multiple regional climate models over East Asia, vulnerable to future climate change. For temperature, internal variability and model uncertainty were the main factors affecting the near-term projections. The scenario uncertainty continued to increase and was estimated to be the dominant factor affecting the uncertainty after the mid-term projections. Although precipitation has the same main uncertainty factors as the temperature in the near-term projections, it significantly differs from temperature because the internal variability notably contributes to the fraction to the total variance, even in the long-term projections. The internal variability of the temperature and precipitation in the near-term projections was predicted to be larger in Korea than that in East Asia. This was confirmed by regional climate models as well as previous studies using global climate models as to the importance of internal variability at smaller regional scales during the near-term projections. This study is of significance because it provides new possibilities with respect to the consideration of climate uncertainties to the establishment of climate change policies in more detail on the regional scale.

Background & AimsFusobacterium nucleatum (FN) plays a pivotal role in the development and progression of colorectal cancer by modulating antitumor immune responses. However, the impact of FN on immune regulation in the tumor microenvironment has not been fully elucidated.MethodsThe abundance of FN was measured in 99 stage III CRC tumor tissues using quantitative polymerase chain reaction. Gene expression profiles were assessed and annotated using consensus molecular subtypes (CMS), Gene Ontology (GO) analysis, and deconvolution of individual immune cell types in the context of FN abundance. Immune profiling for tumor infiltrating T cells isolated from human tumor tissues was analyzed using flow cytometry. Ex vivo tumor-infiltrating T cells were stimulated in the presence or absence of FN to determine the direct effects of FN on immune cell phenotypes.ResultsGene expression profiles, CMS composition, abundance of immune cell subtypes, and survival outcomes differed depending on FN infection. We found that FN infection was associated with poorer disease-free survival and overall survival in stage III CRC patients. FN infection was associated with T cell depletion and enrichment of exhausted CD8+ and FoxP3+ regulatory T cells in the tumor microenvironment. The presence of FN in tumors was correlated with a suppressive tumor microenvironment in a T cell-dependent manner.ConclusionFN enhanced the suppressive immune microenvironment with high depletion of CD8+ T cells and enrichment of FoxP3+ regulatory T cells in human colorectal cancer cases. Our findings suggest a potential association for FN in adaptive immunity, with biological and prognostic implications.

We selected the land area over East Asia (100°E–150°E and 20°N–50°N) as the analysis domain, which includes Korea, Japan, China (except for the western arid region), and parts of Mongolia and Russia. The major analysis variables are the daily mean surface temperature (TAS) and daily precipitation (PR). Multiple RCM datasets with 25 km horizontal spatial resolution forced by three Climate Model Intercomparison Project phase 5 (CMIP5) GCMs (HadGEM2-AO, MPI-ESM-LR, and GFDL-ESM-2M) included in the CORDEX-East Asia phase Ⅱ project were used to estimate the uncertainties of future climate projections. The historical experiment for 1981–2005 and Representative Concentration Pathway (RCP) 2.6 and RCP 8.5 scenarios for 2006–2099 were applied in this study. The variance scaling (VS) and quantile mapping of the entire period (QME) were applied to the TAS and PR for each grid, respectively.

BackgroundExtracellular vesicles secreted by tumor cells contain double-stranded DNA called extracellular vesicle DNA (evDNA). EvDNA is genomic DNA that reflects cancer driver mutations. However, the significance of evDNA analysis in the diagnosis and surveillance of colon cancer remains unclear. This study aimed to investigate the clinical utility of extracellular vesicles and evDNA isolated from the plasma of colon cancer patients harboring KRAS G12D and G13D mutations.MethodsCell-free DNA (cfDNA) and evDNA were collected from the plasma of 30 patients with colon cancer. KRAS mutation status (G12D and G13D) was detected using a droplet digital polymerase chain reaction assay (ddPCR). Sensitivity and specificity were evaluated in patients with wild-type KRAS tumors. Mutation status was correlated with carcinoembryonic antigen (CEA) levels and overall survival (OS).ResultsThirty cfDNA and evDNA pairs showed a KRAS fractional abundance (FA) ranging from 0 to 45.26% and 0 to 83.81%, respectively. When compared with eight wild-type KRAS samples, cfDNA exhibited 70% sensitivity and 100% specificity, whereas evDNA achieved 76.67% sensitivity and 100% specificity. The concentration of evDNA was significantly lower than that of cfDNA, but it obtained a higher FA than cfDNA, while showing a positive correlation with CEA.ConclusionsOur findings demonstrate the feasibility of evDNA as a complementary tool to aid current methods of patient evaluation in the diagnosis and surveillance of colon cancer.

Extracellular vesicles secreted by tumor cells contain double-stranded DNA called extracellular vesicle DNA (evDNA). EvDNA is genomic DNA that reflects cancer driver mutations. However, the significance of evDNA analysis in the diagnosis and surveillance of colon cancer remains unclear. This study aimed to investigate the clinical utility of extracellular vesicles and evDNA isolated from the plasma of colon cancer patients harboringCell-free DNA (cfDNA) and evDNA were collected from the plasma of 30 patients with colon cancer.Thirty cfDNA and evDNA pairs showed aOur findings demonstrate the feasibility of evDNA as a complementary tool to aid current methods of patient evaluation in the diagnosis and surveillance of colon cancer.

BackgroundAlthough emerging evidence suggests that periodontitis might increase the risk of cancer, comorbidity and lifestyle behaviors, such as smoking and body mass index (BMI), may have confounded this reported association. This study aimed to investigate whether chronic periodontitis is associated with cancer risk using a large, nationwide database.MethodsWe conducted a population-based, retrospective cohort study using data from the Korean National Health Insurance Cohort Database obtained between January 2003 and December 2015. We included 713,201 individuals without a history of cancer who were followed up to 10 years. Confounding factors included demographic factors (age, sex, income, and residential area), lifestyle behaviors (smoking history and BMI), and comorbidities, such as hypertension, diabetes, heart failure, and pulmonary disease, using the Charlson Comorbidity Index. Multivariable Cox regression analysis was applied to estimate the adjusted hazard ratio (aHR) for cancer risk.ResultsOf the 713,201 participants, 53,075 had periodontitis and were placed in the periodontitis group; the remaining 660,126 individuals were included as the control group. Overall, the cumulative incidence of cancer in the periodontitis group was 2.2 times higher than that in the control group. The periodontitis group had an increased risk of total cancer compared to the control group after adjusting for age, sex, comorbidities, BMI, and smoking history (aHR, 1.129; 95% confidence interval [CI], 1.089-1.171; PP=0.0037), colon cancer (aHR, 1.129; 95% CI, 1.029-1.239; P=0.0105), lung cancer (aHR, 1.127; 95% CI, 1.008-1.260; P=0.0353), bladder cancer (aHR, 1.307; 95% CI, 1.071-1.595; P=0.0085), thyroid cancer (aHR, 1.191; 95% CI, 1.085-1.308; P=0.0002), and leukemia (aHR, 1.394; 95% CI, 1.039-1.872; P=0.0270). There was no significant association between the development of secondary malignancy and periodontitis in cancer survivors who were alive 5 years after they were diagnosed with the primary malignancy.ConclusionsPeriodontal disease, including periodontitis, was associated with increased risk of cancer, which persisted after controlling for confounding factors. Further prospective research is warranted to establish a causal relationship.

Statistical bias correction (BC) is a widely used tool to post-process climate model biases for heat-stress impact studies, which are often based on indices calculated from multiple dependent variables. This study compares five bias correction methods (four univariate and one multivariate) with two applying strategies (direct and indirect) for correcting two heat-stress indices with different dependencies on temperature and relative humidity, using multiple Regional Climate Model simulations over South Korea. It would be helpful for reducing the ambiguity involved in the practical application of BC for climate modeling as well as end-user communities. Our results demonstrate that the multivariate approach can improve the corrected inter-variable dependence and therefore benefit the indirect correction of heat-stress indices that depend on the adjustment of individual components, especially those relying equally on multiple drivers. On the other hand, the direct correction of multivariate indices using the Quantile Delta Mapping univariate approach can also produce a comparable performance in the corrected heat-stress indices. However, our results also indicate that attention should be paid to the non-stationarity of bias brought by climate sensitivity in the modeled data, which may affect the bias-corrected results unsystematically. Careful interpretation of the correction process is required for an accurate heat-stress impact assessment.

To assess the effect of local ablative therapy (LAT) on overall survival in patients with lung metastases from colorectal cancer (CRC) compared with patients treated with systemic therapy.CRC affects approximately 1.4 million individuals worldwide every year. The lungs are commonly affected by CRC, and there is no treatment standard for a secondary lung metastasis from CRC.This longitudinal, retrospective cohort study (2010-2018) quantified the pulmonary and extrapulmonary tumor burden of 1143 patients by retrospectively reviewing computed tomography images captured at diagnosis. A comprehensive multidisciplinary approach informed how and when surgery and/or stereotactic body radiotherapy was administered.Among 1143 patients, 473 patients (41%) received LAT, with surgery first (n = 421) or stereotactic ablative radiation therapy first (n = 52) either at the time of diagnosis (n = 288), within 1 year (n = 132), or after 1 year (n = 53). LAT was repeated in 158 patients (33.4%, 384 total sessions) when new lung metastases were detected. The 5- and 10-year survival rates for patients treated with LAT (71.2% and 64.0%, respectively) were significantly higher than those of patients treated with systemic therapy alone (14.2% and 10.0%, respectively; P0.001). The overall survival of patients who received LAT intervention increased as the total tumor burden decreased.A high long-term survival rate was achievable in a significant portion of patients with lung metastasis from CRC by the timely administrations of LAT to standard systemic therapy. The tumor burden and LAT feasibility should be included in a discussion during the follow-up period.

The combination of oxaliplatin and fluoropyrimidine for 6 months is one of the standard options for adjuvant therapy for high-risk stage II and III colorectal cancers (CRCs). The optimal duration of oxaliplatin to diminish neurotoxicity without compromising efficacy needs to be clarified.This open-label, randomized, phase III, noninferiority trial randomly assigned patients with high-risk stage II and III CRC to 3 and 6 months of oxaliplatin with 6 months of fluoropyrimidine groups (3- and 6-month arms, respectively). The primary end point was disease-free survival (DFS), and the noninferiority margin was a hazard ratio (HR) of 1.25.In total, 1,788 patients were randomly assigned to the 6-month (n = 895) and 3-month (n = 893) arms, and 83.6% in the 6-month arm and 85.7% in the 3-month arm completed the treatment. The neuropathy rates with any grade were higher in the 6-month arm than in the 3-month arm (69.5%This study suggests that adding 3 months of oxaliplatin to 6 months of capecitabine could be considered an alternative adjuvant treatment for stage III CRC (ClinicalTrials.gov identifier: NCT01092481).

The canonical mutations in gastrointestinal stromal tumors (GISTs) are typically activating mutations in KIT and platelet-derived growth factor receptor alpha (PDGFRA). GISTs with non-canonical mutations are a heterogeneous group. Here, we examined tropomyosin-related kinase (TRK) fusion in GIST cases without KIT/PDGFRA mutations (KIT/PDGFRA wild-type (WT) GISTs). We retrospectively analyzed patients who were diagnosed with GISTs at the Yonsei Cancer Center, Severance Hospital, between January 1998 and December 2016. Thirty-one patients with KIT/PDGFRA WT GISTs were included in the analysis. TRK expression in tumor samples was assessed by pan-TRK immunohistochemistry (IHC), and the neurotrophic tyrosine receptor kinase (NTRK: the gene encoding TRK) rearrangement was analyzed by fluorescence in situ hybridization (FISH). IHC analyses revealed that five cases in this cohort exhibited a weak to moderate TRK expression. NTRK1 fusions were detected in three tumor samples, and two samples harbored NTRK3 fusions. The remaining 26 samples did not harbor NTRK fusions. Two types of NTRK fusions were detected, and the overall NTRK fusion frequency in KIT/PDGFRA WT GIST cases was 16% (5/31). Our data provide insights into the molecular alterations underpinning KIT/PDGFRA WT GISTs. More effort should be devoted to improve methods to identify this distinct disease subtype within the KIT/PDGFRA WT GIST group.

Background Skeletal muscle and BMI are essential prognostic factors for survival in colorectal cancer (CRC). However, there is a lack of understanding due to scarce studies on the continuous aspects of these variables. Objective This study aimed to evaluate the prognostic impact of the initial status and trajectories of muscle and BMI on overall survival (OS) and assess whether these 4 profiles within 1 year can represent the profiles 6 years later. Methods We analyzed 4056 newly diagnosed patients with CRC between 2010 to 2020. The volume of the muscle with 5-mm thickness at the third lumbar spine level was measured using a pretrained deep learning algorithm. The skeletal muscle volume index (SMVI) was defined as the muscle volume divided by the square of the height. The correlation between BMI status at the first, third, and sixth years of diagnosis was analyzed and assessed similarly for muscle profiles. Prognostic significances of baseline BMI and SMVI and their 1-year trajectories for OS were evaluated by restricted cubic spline analysis and survival analysis. Patients were categorized based on these 4 dimensions, and prognostic risks were predicted and demonstrated using heat maps. Results Trajectories of SMVI were categorized as decreased (812/4056, 20%), steady (2014/4056, 49.7%), or increased (1230/4056, 30.3%). Similarly, BMI trajectories were categorized as decreased (792/4056, 19.5%), steady (2253/4056, 55.5%), or increased (1011/4056, 24.9%). BMI and SMVI values in the first year after diagnosis showed a statistically significant correlation with those in the third and sixth years (P30 kg/m2 with a low SMVI at the time of diagnosis resulted in the highest mortality risk. We observed improved survival in patients with increased muscle mass without BMI loss compared to those with steady muscle mass and BMI. Conclusions Profiles within 1 year of both BMI and muscle were surrogate indicators for predicting the later profiles. Continuous trajectories of body and muscle mass are independent prognostic factors of patients with CRC. An automatic algorithm provides a unique opportunity to conduct longitudinal evaluations of body compositions. Further studies to understand the complicated natural courses of muscularity and adiposity are necessary for clinical application.

The aim of our study is to evaluate the clinical efficacy of durvalumab in patients with microsatellite instability-high/mismatch repair-deficient (MSI-H/dMMR) or polymerase epsilon (POLE)-mutated metastatic or unresectable colorectal cancer (mCRC) who had disease progression after standard chemotherapy. This prospective, open-label, multicenter, phase II study enrolled patients with mCRC harboring MSI-H/dMMR or POLE mutations treated with at least one prior line of therapy. The participants received durvalumab (1500 mg) every 4 weeks intravenously. The primary endpoint was the objective response rate (ORR). Of the 33 patients, 30 had MSI-H/dMMR and 3 had POLE-mutated microsatellite stable (MSS) CRC. With a median follow-up duration of 11.2 months (95% confidence interval [CI]: 7.3-15.0), the ORR was 42.4% (95% CI: 25.5-60.8). Among three patients with POLE-mutated CRC, one patient who had an exonuclease domain mutation (EDM) achieved an objective response, but the others with mutations in the non-exonuclease domain had progressive disease. Overall, the median duration of response was not reached and 85.7% of the responses were ongoing at data cutoff. The progression-free survival rate of 12 months was 58.2% (95% CI: 39.0-73.1) and the 12-month overall survival rate was 68.3% (95% CI: 48.8-81.7). Grade 3 treatment-related adverse events occurred in 36.4% of the patients and were manageable. In conclusion, durvalumab showed promising clinical activity with encouraging response rates and satisfactory survival outcomes in mCRC patients with MSI-H/dMMR or POLE EDM. In patients with POLE-mutated mCRC, clinical response to durvalumab may be restricted to those with EDM.

Background: Although cancer patients are increasingly admitted to the intensive care unit (ICU) for cancer- or treatment-related complications, improved mortality prediction remains a big challenge. This study describes a new ML-based mortality prediction model for critically ill cancer patients admitted to ICU. Patients and Methods: We developed CanICU, a machine learning-based 28-day mortality prediction model for adult cancer patients admitted to ICU from Medical Information Mart for Intensive Care (MIMIC) database in the USA (n = 766), Yonsei Cancer Center (YCC, n = 3571), and Samsung Medical Center in Korea (SMC, n = 2563) from 2 January 2008 to 31 December 2017. The accuracy of CanICU was measured using sensitivity, specificity, and area under the receiver operating curve (AUROC). Results: A total of 6900 patients were included, with a 28-day mortality of 10.2%/12.7%/36.6% and a 1-year mortality of 30.0%/36.6%/58.5% in the YCC, SMC, and MIMIC-III cohort. Nine clinical and laboratory factors were used to construct the classifier using a random forest machine-learning algorithm. CanICU had 96% sensitivity/73% specificity with the area under the receiver operating characteristic (AUROC) of 0.94 for 28-day, showing better performance than current prognostic models, including the Acute Physiology and Chronic Health Evaluation (APACHE) or Sequential Organ Failure Assessment (SOFA) score. Application of CanICU in two external data sets across the countries yielded 79–89% sensitivity, 58–59% specificity, and 0.75–0.78 AUROC for 28-day mortality. The CanICU score was also correlated with one-year mortality with 88–93% specificity. Conclusion: CanICU offers improved performance for predicting mortality in critically ill cancer patients admitted to ICU. A user-friendly online implementation is available and should be valuable for better mortality risk stratification to allocate ICU care for cancer patients.

In the original article [...]