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The breakthrough therapy designation (BTD) process was created to expedite clinical development timelines for drugs intended to treat serious conditions and preliminary clinical evidence indicates the drug may demonstrate substantial improvement over existing therapies. This analysis demonstrates that BTD is a valuable tool for expediting approval of promising therapies in oncology. By comparing drugs indicated to treat non–small cell lung cancer (NSCLC) approved with BTD or without BTD between January 2013 and October 2021, BTD drugs reduced the risk of death by a median of 31% and progression by a median of 48%, while drugs never receiving BTD reduced the risk of death and progression by a median of 15% and 41.9%, respectively. These findings show that BTD criteria accurately identify drugs that improve long-term outcomes for patients with cancer and warrant coordinated efforts to ensure timely coverage decisions and access for patients.

PURPOSE This study compared real-world end points extracted from the Cancer Analysis System (CAS), a national cancer registry with linkage to national mortality and other health care databases in England, with those from diverse US oncology data sources, including electronic health care records, insurance claims, unstructured medical charts, or a combination, that participated in the Friends of Cancer Research Real-World Evidence Pilot Project 1.0. Consistency between data sets and between real-world overall survival (rwOS) was assessed in patients with immunotherapy-treated advanced non–small-cell lung cancer (aNSCLC). PATIENTS AND METHODS Patients with aNSCLC, diagnosed between January 2013 and December 2017, who initiated treatment with approved programmed death ligand-1 (PD-[L]1) inhibitors until March 2018 were included. Real-world end points, including rwOS and real-world time to treatment discontinuation (rwTTD), were assessed using Kaplan-Meier analysis. A synthetic data set, Simulacrum, on the basis of conditional random sampling of the CAS data was used to develop and refine analysis scripts while protecting patient privacy. RESULTS Characteristics (age, sex, and histology) of the 2,035 patients with immunotherapy-treated aNSCLC included in the CAS study were broadly comparable with US data sets. In CAS, a higher proportion (46.7%) of patients received a PD-(L)1 inhibitor in the first line than in US data sets (18%-30%). Median rwOS (11.4 months; 95% CI, 10.4 to 12.7) and rwTTD (4.9 months; 95% CI, 4.7 to 5.1) were within the range of US-based data sets (rwOS, 8.6-13.5 months; rwTTD, 3.2-7.0 months). CONCLUSION The CAS findings were consistent with those from US-based oncology data sets. Such consistency is important for regulatory decision making. Differences observed between data sets may be explained by variation in health care settings, such as the timing of PD-(L)1 approval and reimbursement, and data capture.

Background Tumor mutational burden (TMB) measurements aid in identifying patients who are likely to benefit from immunotherapy; however, there is empirical variability across panel assays and factors contributing to this variability have not been comprehensively investigated. Identifying sources of variability can help facilitate comparability across different panel assays, which may aid in broader adoption of panel assays and development of clinical applications. Materials and methods Twenty-nine tumor samples and 10 human-derived cell lines were processed and distributed to 16 laboratories; each used their own bioinformatics pipelines to calculate TMB and compare to whole exome results. Additionally, theoretical positive percent agreement (PPA) and negative percent agreement (NPA) of TMB were estimated. The impact of filtering pathogenic and germline variants on TMB estimates was assessed. Calibration curves specific to each panel assay were developed to facilitate translation of panel TMB values to whole exome sequencing (WES) TMB values. Results Panel sizes >667 Kb are necessary to maintain adequate PPA and NPA for calling TMB high versus TMB low across the range of cut-offs used in practice. Failure to filter out pathogenic variants when estimating panel TMB resulted in overestimating TMB relative to WES for all assays. Filtering out potential germline variants at >0% population minor allele frequency resulted in the strongest correlation to WES TMB. Application of a calibration approach derived from The Cancer Genome Atlas data, tailored to each panel assay, reduced the spread of panel TMB values around the WES TMB as reflected in lower root mean squared error (RMSE) for 26/29 (90%) of the clinical samples. Conclusions Estimation of TMB varies across different panels, with panel size, gene content, and bioinformatics pipelines contributing to empirical variability. Statistical calibration can achieve more consistent results across panels and allows for comparison of TMB values across various panel assays. To promote reproducibility and comparability across assays, a software tool was developed and made publicly available.

In prior work, Friends of Cancer Research convened multiple data partners to establish standardized definitions for oncology real-world end points derived from electronic health records (EHRs) and claims data. Here, we assessed the performance of real-world overall survival (rwOS) from data sets sourced from EHRs by evaluating the ability of the end point to reflect expected differences from a previous randomized controlled trial across five data sources, after applying inclusion/exclusion criteria. The KEYNOTE-189 clinical trial protocol of platinum doublet chemotherapy (chemotherapy) vs. programmed cell death protein 1 (PD-1) in combination with platinum doublet chemotherapy (PD-1 combination) in first-line nonsquamous metastatic non-small cell lung cancer guided retrospective cohort selection. The Kaplan-Meier product limit estimator was used to calculate 12-month rwOS with 95% confidence intervals (CIs) in each data source. Cox proportional hazards models estimated hazard ratios (HRs) and associated 95% CIs, controlled for prognostic factors. Once the inclusion/exclusion criteria were applied, the five resulting data sets included 155 to 1,501 patients in the chemotherapy cohort and 36 to 405 patients in the PD-1 combination cohort. Twelve-month rwOS ranged from 45% to 58% in the chemotherapy cohort and 44% to 68% in the PD-1 combination cohort. The adjusted HR for death ranged from 0.80 (95% CI: 0.69, 0.93) to 1.15 (95% CI: 0.71, 1.85), controlling for age, gender, performance status, and smoking status. This study yielded insights regarding data capture, including ability of real-world data to precisely identify patient populations and the impact of criteria on end points. Sensitivity analyses could elucidate data set-specific factors that drive results.

Legislative and technological advancements over the past decade have given rise to the proliferation of healthcare data generated from routine clinical practice, often referred to as real-world data (RWD). These data have piqued the interest of healthcare stakeholders due to their potential utility in generating evidence to support clinical and regulatory decision making. In the oncology setting, studies leveraging RWD offer distinct advantages that are complementary to randomized controlled trials (RCTs). They also permit the conduct of investigations that may not be possible through prospective designs due to ethics or feasibility. Despite its promise, the use of RWD for the generation of clinical evidence remains controversial due to concerns of unmeasured confounding and other sources of bias that must be carefully addressed in the study design and analysis. To facilitate a better understanding of when RWD can provide reliable conclusions on drug effectiveness, we seek to conduct 10 RWD-based studies that emulate RCTs in oncology using a systematic, protocol-driven approach described herein. Results of this investigation will help inform clinical, scientific, and regulatory stakeholders on the applications of RWD in the context of product labeling expansion, drug safety, and comparative effectiveness in oncology.

Background Households represent important settings for transmission of influenza and other respiratory viruses. Current influenza diagnosis and treatment relies upon patient visits to healthcare facilities, which may lead to under‐diagnosis and treatment delays. This study aimed to assess the feasibility of an at‐home approach to influenza diagnosis and treatment via home testing, telehealth care, and rapid antiviral home delivery. Methods We conducted a pilot interventional study of remote influenza diagnosis and treatment in Seattle‐area households with children during the 2019‐2020 influenza season using pre‐positioned nasal swabs and home influenza tests. Home monitoring for respiratory symptoms occurred weekly; if symptoms were reported within 48 hours of onset, participants collected mid‐nasal swabs and used a rapid home‐based influenza immunoassay. An additional home‐collected swab was returned to a laboratory for confirmatory influenza RT‐PCR testing. Baloxavir antiviral treatment was prescribed and delivered to symptomatic and age‐eligible participants, following a telehealth encounter. Results 124 households comprising 481 individuals self‐monitored for respiratory symptoms, with 58 home tests administered. 12 home tests were positive for influenza, of which eight were true positives confirmed by RT‐PCR. The sensitivity and specificity of the home influenza test were 72.7% and 96.2%, respectively. There were eight home deliveries of baloxavir, with 7 (87.5%) occurring within 3 hours of prescription and all within 48 hours of symptom onset. Conclusions We demonstrate the feasibility of self‐testing combined with rapid home delivery of influenza antiviral treatment. This approach may be an important control strategy for influenza epidemics and pandemics.

Purpose: Restrictive clinical trial eligibility criteria (EC) limit the number of patients who can enroll and potentially benefit from protocol-driven, investigational treatment plans and reduce the generalizability of trial results to the broader population. Following publication of expert stakeholder recommendations for broadening EC in 2017, the American Society of Clinical Oncology (ASCO) and Friends of Cancer Research (Friends) convened working groups to produce additional recommendations and analyze the potential impact on clinical trials using real-world data. Experimental Design: Multistakeholder working groups were appointed by an ASCO-Friends leadership group to propose recommendations for more inclusive EC related to: washout periods, concomitant medications, prior therapies, laboratory reference ranges and test intervals, and performance status. Results: The four working groups, ASCO Board of Directors, and Friends leadership support the recommendations included in this statement to modernize EC related to washout periods, concomitant medications, prior therapies, laboratory references ranges and test intervals, and performance status to make trial populations more inclusive and representative of cancer patient populations. Conclusions: Implementation of the recommendations is intended to result in greater ease of determining patient eligibility. Increased opportunities for patient participation in research will help address longstanding underrepresentation of certain groups in clinical trials and produce evidence that is more informative for a broader patient population. More patients eligible will also likely speed clinical trial accrual. See related commentary by Giantonio, p. 2369

Breakthrough therapy designation (BTD) is a valuable tool for expediting approval of promising therapies in oncology. Expediting drug development and review is time and resource intensive, so it is imperative to assess the performance of BTD and determine whether the criteria identify promising drugs that lead to improved outcomes for patients. This perspective provides a comparison of clinical outcomes data and National Comprehensive Cancer Network (NCCN) clinical guidelines for drugs indicated to treat non-small cell lung cancer (NSCLC) approved with BTD or without BTD between January 2013 and October 2021. Across the 31 approvals supported by data from randomized controlled trials, with the primary or co-primary endpoints of progression-free survival and/or overall survival, BTD drugs reduced the risk of death by a median of 31% and progression by a median of 48%, while drugs never receiving BTD ("Never BTD") reduced the risk of death and progression by a median of 15% and 41.9%, respectively. More BTD drugs received a NCCN recommendation in the highest category of evidence (Category 1) than Never BTD drugs, and a greater proportion of BTD drugs were considered "preferred" compared to Never BTD drugs. In the context of this improved value, we provide considerations for establishing an expedited pathway for coverage decisions on BTD drugs to support timely access for patients. These results suggest the qualifying criteria for BTD identify drugs that improve outcomes for patients with cancer, and thus, may benefit from mechanisms that expedite processes to ensure timely coverage decisions and access for patients.

Objective: Reducing antibiotic overuse is a point of emphasis of the Centers for Disease Control and Prevention. Inappropriate use of antibiotics is cited as a key driver of antibiotic resistance. Despite this, both telemedicine and traditional in-person medical care struggle to meet national guidelines. This study evaluates antibiotic prescribing practices at 98point6, a Seattle-based provider of real-time, text-based primary care. This paper reviews a novel combination of machine learning with a physician-led virtual platform and smartphone interface to exceed published benchmarks for the avoidance of antibiotics in the treatment of bronchitis. Design: This retrospective cohort study looks at patients ages 18–64 who were evaluated and treated using real-time, text-based care. Cases in which patients were diagnosed with “acute bronchitis/bronchiolitis” between December 1, 2019 and November 30, 2020 were analyzed. Visits were categorized by whether systemic antibiotics were or were not given. Setting: This telemedicine provider provides service to patients ages 1 and above in all 50 states and the District of Columbia. The cohort that is present was drawn from that population. Participants: A total of 1,238 consecutive patients ages 18–64 who presented for medical care during the time period. Interventions: This is a retrospective cohort. No direct intervention was undertaken. Patients received standard care for the evaluation and treatment of upper respiratory symptoms. Main Outcome Measures: The results are presented as descriptive statistics with demographic information and compared to published reports of appropriate antibiotic use for the treatment of bronchitis. Results: Of the 1,238 visits with a bronchitis/bronchiolitis diagnosis, 99 (8.0%) were treated with prescribed systemic antibiotics. The rate of antibiotic avoidance of 92.0% compares favorably with published benchmarks from the National Committee for Quality Assurance and is significantly lower than rates in previously published samples for telemedicine, primary care, and urgent care. Conclusion: Real-time text-based care resulted in a high rate of adherence to the established standard for the treatment of bronchitis, greatly exceeding benchmarks and published results from both telemedicine and in-person medical practice.

The equations for double-mean, form-induced and spatially averaged turbulent energy budgets are employed to analyse data from direct numerical simulations of turbulent open-channel flows over trans...

Background Tumor mutational burden (TMB) is an emerging biomarker used to identify patients who are more likely to benefit from immuno-oncology therapy. Aside from various unsettled technical aspects, biological variables such as tumor cell content and intratumor heterogeneity may play an important role in determining TMB. Methods TMB estimates were determined applying the TruSight Oncology 500 targeted sequencing panel. Spatial and temporal heterogeneity was analyzed by multiregion sequencing (two to six samples) of 24 pulmonary adenocarcinomas and by sequencing a set of matched primary tumors, locoregional lymph node metastases, and distant metastases in five patients. Results On average, a coding region of 1.28 Mbp was covered with a mean read depth of 609x. Manual validation of the mutation-calls confirmed a good performance, but revealed noticeable misclassification during germline filtering. Different regions within a tumor showed considerable spatial TMB variance in 30% (7 of 24) of the cases (maximum difference, 14.13 mut/Mbp). Lymph node–derived TMB was significantly lower (p = 0.016). In 13 cases, distinct mutational profiles were exclusive to different regions of a tumor, leading to higher values for simulated aggregated TMB. Combined, intratumor heterogeneity and the aggregated TMB could result in divergent TMB designation in 17% of the analyzed patients. TMB variation between primary tumor and distant metastases existed but was not profound. Conclusions Our data show that, in addition to technical aspects such as germline filtering, the tumor content and spatially divergent mutational profiles within a tumor are relevant factors influencing TMB estimation, revealing limitations of single-sample–based TMB estimations in a clinical context.

Glaucoma is one of the leading causes of blindness, and there is an ongoing need for new therapies. Recent studies indicate that cell transplantation using Müller glia may be beneficial, but there is a need for novel sources of cells to provide therapeutic benefit. In this study, we have isolated Müller glia from retinal organoids formed by human induced pluripotent stem cells (hiPSCs) in vitro and have shown their ability to partially restore visual function in rats depleted of retinal ganglion cells by NMDA. Based on the present results, we suggest that Müller glia derived from retinal organoids formed by hiPSC may provide an attractive source of cells for human retinal therapies, to prevent and treat vision loss caused by retinal degenerative conditions. Stem Cells Translational Medicine 2019;8:775–784

Characterization of tumors utilizing next‐generation sequencing methods, including assessment of the number of somatic mutations (tumor mutational burden [TMB]), is currently at the forefront of the field of personalized medicine. Recent clinical studies have associated high TMB with improved patient response rates and survival benefit from immune checkpoint inhibitors; hence, TMB is emerging as a biomarker of response for these immunotherapy agents. However, variability in current methods for TMB estimation and reporting is evident, demonstrating a need for standardization and harmonization of TMB assessment methodology across assays and centers. Two uniquely placed organizations, Friends of Cancer Research (Friends) and the Quality Assurance Initiative Pathology (QuIP), have collaborated to coordinate efforts for international multistakeholder initiatives to address this need. Friends and QuIP, who have partnered with several academic centers, pharmaceutical organizations, and diagnostic companies, have adopted complementary, multidisciplinary approaches toward the goal of proposing evidence‐based recommendations for achieving consistent TMB estimation and reporting in clinical samples across assays and centers. Many factors influence TMB assessment, including preanalytical factors, choice of assay, and methods of reporting. Preliminary analyses highlight the importance of targeted gene panel size and composition, and bioinformatic parameters for reliable TMB estimation. Herein, Friends and QuIP propose recommendations toward consistent TMB estimation and reporting methods in clinical samples across assays and centers. These recommendations should be followed to minimize variability in TMB estimation and reporting, which will ensure reliable and reproducible identification of patients who are likely to benefit from immune checkpoint inhibitors.

Background To date, no immunological data on COVID-19 heterologous vaccination schedules in humans have been reported. We assessed the immunogenicity and reactogenicity of BNT162b2 (Comirnaty, BioNTech, Mainz, Germany) administered as second dose in participants primed with ChAdOx1-S (Vaxzevria, AstraZeneca, Oxford, UK). Methods We did a phase 2, open-label, randomised, controlled trial on adults aged 18–60 years, vaccinated with a single dose of ChAdOx1-S 8–12 weeks before screening, and no history of SARS-CoV-2 infection. Participants were randomly assigned (2:1) to receive either BNT162b2 (0·3 mL) via a single intramuscular injection (intervention group) or continue observation (control group). The primary outcome was 14-day immunogenicity, measured by immunoassays for SARS-CoV-2 trimeric spike protein and receptor binding domain (RBD). Antibody functionality was assessed using a pseudovirus neutralisation assay, and cellular immune response using an interferon-γ immunoassay. The safety outcome was 7-day reactogenicity, measured as solicited local and systemic adverse events. The primary analysis included all participants who received at least one dose of BNT162b2 and who had at least one efficacy evaluation after baseline. The safety analysis included all participants who received BNT162b2. This study is registered with EudraCT (2021-001978-37) and ClinicalTrials.gov (NCT04860739), and is ongoing. Findings Between April 24 and 30, 2021, 676 individuals were enrolled and randomly assigned to either the intervention group (n=450) or control group (n=226) at five university hospitals in Spain (mean age 44 years [SD 9]; 382 [57%] women and 294 [43%] men). 663 (98%) participants (n=441 intervention, n=222 control) completed the study up to day 14. In the intervention group, geometric mean titres of RBD antibodies increased from 71·46 BAU/mL (95% CI 59·84–85·33) at baseline to 7756·68 BAU/mL (7371·53–8161·96) at day 14 (p

Purpose: In clinical research, eligibility criteria promote patient safety and optimize the evidence generated from clinical trials. However, overly stringent eligibility criteria, including laboratory requirements, may limit enrollment, resulting in delayed trial completion and potentially limiting applicability of trial results to a general practice population. Experimental Design: Starting in 2018, a working group consisting of experts in direct patient care, the FDA, industry, and patient advocacy developed recommendations to guide the optimal use of laboratory reference ranges and testing intervals in clinical trial eligibility criteria and study procedures. The working group evaluated current eligibility criteria across different clinical trial phases and performed a literature review to evaluate the impact of and justification for laboratory test eligibility requirements and testing intervals in clinical trials. Recommendations were developed on the basis of the goals of promoting safety and optimizing the evidence generated, while also expanding eligibility and applicability, and minimizing excess burden of trial participation. Results: In general, we found little variation over time and trial phase in laboratory test requirements, suggesting that these eligibility criteria are not refined according to ongoing clinical experience. We propose recommendations to optimize the use of laboratory tests when considering eligibility criteria. Conclusions: Tailoring the use of laboratory test requirements and testing intervals may increase the number and diversity of patients in clinical trials and provide clinical data that more closely represent the general practice populations. See related commentary by Giantonio, p. 2369

BackgroundHouseholds represent important settings for transmission of influenza and other respiratory viruses. Current influenza diagnosis and treatment relies upon patient visits to healthcare facilities, which may lead to under-diagnosis and treatment delays. This study aimed to assess the feasibility of an at-home approach to influenza diagnosis and treatment via home testing, telehealth care, and rapid antiviral home delivery.MethodsWe conducted a pilot interventional study of remote influenza diagnosis and treatment in Seattle-area households with children during the 2019-2020 influenza season using pre-positioned nasal swabs and home influenza tests. Home monitoring for respiratory symptoms occurred weekly; if symptoms were reported within 48 hours of onset, participants collected mid-nasal swabs and used a rapid home-based influenza immunoassay. An additional home-collected swab was returned to a laboratory for confirmatory influenza RT-PCR testing. Baloxavir antiviral treatment was prescribed and delivered to symptomatic and age-eligible participants, following a telehealth encounter.Results124 households comprising 481 individuals self-monitored for respiratory symptoms, with 58 home tests administered. 12 home tests were positive for influenza, of which 8 were true positives confirmed by RT-PCR. The sensitivity and specificity of the home influenza test was 72.7% and 96.2%, respectively. There were 8 home deliveries of baloxavir, with 7 (87.5%) occurring within 3 hours of prescription, and all within 48 hours of symptom onset.ConclusionsWe demonstrate the feasibility of self-testing combined with rapid home delivery of influenza antiviral treatment. This approach may be an important control strategy for influenza epidemics and pandemics.SummaryIn this pilot study, 481 individuals self-monitored for respiratory symptoms. Of 58 home tests, 12 were influenza-positive. There were 8 baloxavir home deliveries within 48 hours of illness onset. A home-based approach to influenza diagnosis and treatment could be feasible.

Several benefits have been brought about by using Minimally Invasive Surgery (MIS), including faster procedure times, reduction of patient pain, and reductions in complications intraoperatively and postoperatively. However, some new techniques in MIS for colon cancer are technically difficult to perform using currently available instruments. Robotic systems for treatment of cancer in the lower Gastrointestinal (GI) tract have not shown performance that has translated into regular adoption. This thesis describes the creation of soft parallel robots for MIS that provide a different approach to the devices in the literature. To the author’s knowledge, this is the first deployable, laser welded, soft, hybrid parallel robot designed for minimally invasive surgery. The field of soft robotics relies on soft materials for the construction of robotic devices and is a growing field of research. A keyword search of soft robotic devices for use in MIS was performed, revealing general trends in the current research. It was found that a majority of devices in research were of continuum type, were moulded with elastomeric materials, and were pneumatically actuated. The literature review helped to shape the manufacturing approach taken in this work, as it had been identified that few devices were low-profile, deployable, or could significantly change their volume when transitioning from an inactive to active state. A laser welding system was designed and built for this purpose, delivering a rapid, low-cost, and adaptable manufacturing method for low-profile, deployable structures and actuators. This thesis describes the first use of this manufacturing technique for creation of soft robotic devices for minimally invasive surgery. A deployable, bimanual, cable-driven parallel robot was manufactured using the laser welding system and showed maximum force exertion capabilities of 8.29 N. A programmatic design approach was used to design the structure of the robot, which highlights the ability to customise the design. The robot was used to successfully perform a procedure with similar steps to Endoscopic Submucosal Dissection (ESD) with an untrained, novice user. The estimated volume change from the undeployed to the deployed state of the robot was approximately 73%. Novel soft hydraulic actuators were designed for use with deployable soft robots and were tested in a variety of configurations, from one Degree Of Freedom (DOF) to three DOFs. This is the first time, to the author’s knowledge, that open loop position control, length estimation based on internal pressure, and collision detection have been demonstrated with this type of actuator. Open loop position control was demonstrated with the soft actuator, achieving RMSE values of 0.47 mm for a single actuator acting against gravity and 0.35 mm when used in an antagonistic configuration. The hysteresis values in each configuration were 0.71 mm and 0.51 mm respectively. The contraction of the soft actuators was estimated based on the internal pressure of the actuators. The RMSE between the estimated contraction and desired contraction was 0.98 mm when applied to the pressure data from the same configuration and 0.76 mm in the hybrid parallel configuration after a correctional offset was applied. The internal pressure in the actuators was used to demonstrate collision detection when the actuators were setup in a hybrid parallel mechanism. 100% of the simulated collisions were detected using a heuristic method that monitored changes in pressure over time and the angle at which the collisions were made could also be estimated. The RMSE between the estimated contact angle and the true angle at which contact was made was 8.22° over a 120° test range, and the method had an R-squared value of 0.95. Finally, a second deployable robot was manufactured that used three of the novel soft actuators to control its end effector. The robot was manufactured rapidly, at low-cost, with the only rigid components being the shaft assembly that delivered the instrument. A user was able to repeatedly trace a circle using the robot and the performance of the robot with a human-in-the-loop to correct its motion online even with the simple construction and control strategy of the robot. Open Access

Background The COVID-19 pandemic remains a significant global threat. However, despite urgent need, there remains uncertainty surrounding best practices for pharmaceutical interventions to treat COVID-19. In particular, conflicting evidence has emerged surrounding the use of hydroxychloroquine and azithromycin, alone or in combination, for COVID-19. The COVID-19 Evidence Accelerator convened by the Reagan-Udall Foundation for the FDA, in collaboration with Friends of Cancer Research, assembled experts from the health systems research, regulatory science, data science, and epidemiology to participate in a large parallel analysis of different data sets to further explore the effectiveness of these treatments. Methods Electronic health record (EHR) and claims data were extracted from seven separate databases. Parallel analyses were undertaken on data extracted from each source. Each analysis examined time to mortality in hospitalized patients treated with hydroxychloroquine, azithromycin, and the two in combination as compared to patients not treated with either drug. Cox proportional hazards models were used, and propensity score methods were undertaken to adjust for confounding. Frequencies of adverse events in each treatment group were also examined. Results Neither hydroxychloroquine nor azithromycin, alone or in combination, were significantly associated with time to mortality among hospitalized COVID-19 patients. No treatment groups appeared to have an elevated risk of adverse events. Conclusion Administration of hydroxychloroquine, azithromycin, and their combination appeared to have no effect on time to mortality in hospitalized COVID-19 patients. Continued research is needed to clarify best practices surrounding treatment of COVID-19.