Efficacy versus effectiveness: The HORIZON Pivotal Fracture Trial and its emulation in Claims Data.

OBJECTIVES: To evaluate the concordance of results between the HORIZON-Pivotal Fracture Trial (PFT) and a non-randomized database study designed to emulate the trial. METHODS: HORIZON-PFT evaluated the efficacy of zoledronic acid vs placebo in reducing the risk of hip fractures and found a 41% risk reduction over a 3-year treatment period (HR = 0.59; 95% CI 0.42 to 0.83). Using two U.S. claims databases from 08/2007 to 12/2020 or 06/2021 we applied eligibility criteria from HORIZON-PFT and identified women with osteoporosis who initiated zoledronic acid or raloxifene as a proxy for placebo. The study protocol was registered on ClinicalTrials.gov (NCT04736693) before inferential analyses. We compared HORIZON-PFT and database study results using prespecified metrics. RESULTS: Due to low adherence in clinical practice, on-treatment follow up was truncated at 18 months in the database study. The hip fracture risk after 18 months was 9.3/1000 in the trial and 8.3/1000 in the database analysis. In the database study, zoledronic acid was associated with a 28% reduction in hip fractures risk compared to raloxifene (HR = 0.72; 95% CI 0.51 to 0.92). The attenuated effect of zoledronic acid in the database study may be explained by its shorter follow-up, as the interpolated estimate of the effect in HORIZON-PFT at 18 months was HRRCT 0.74, nearly identical to the observational estimate HRdatabase 0.72. CONCLUSION: Real-world emulation of the HORIZON-PFT found that zoledronic acid reduced hip fractures risk over an 18-month follow-up period. Limited adherence in clinical practice diminished the magnitude of its preventive effect and precluded long-term estimation of effectiveness in this setting.

A Dynamic Prognostic Model for Identifying Vulnerable COVID-19 Patients at High Risk of Rapid Deterioration.

PURPOSE: We aimed to validate and, if performance was unsatisfactory, update the previously published prognostic model to predict clinical deterioration in patients hospitalized for COVID-19, using data following vaccine availability. METHODS: Using electronic health records of patients ≥18 years, with laboratory-confirmed COVID-19, from a large care-delivery network in Massachusetts, USA, from March 2020 to November 2021, we tested the performance of the previously developed prediction model and updated the prediction model by incorporating data after availability of COVID-19 vaccines. We randomly divided data into development (70%) and validation (30%) cohorts. We built a model predicting worsening in a published severity scale in 24 h by LASSO regression and evaluated performance by c-statistic and Brier score. RESULTS: Our study cohort consisted of 8185 patients (Development: 5730 patients [mean age: 62; 44% female] and Validation: 2455 patients [mean age: 62; 45% female]). The previously published model had suboptimal performance using data after November 2020 (N = 4973, c-statistic = 0.60. Brier score = 0.11). After retraining with the new data, the updated model included 38 predictors including 18 changing biomarkers. Patients hospitalized after Jun 1st, 2021 (when COVID-19 vaccines became widely available in Massachusetts) were younger and had fewer comorbidities than those hospitalized before. The c-statistic and Brier score were 0.77 and 0.13 in the development cohort, and 0.73 and 0.14 in the validation cohort. CONCLUSION: The characteristics of patients hospitalized for COVID-19 differed substantially over time. We developed a new dynamic model for rapid progression with satisfactory performance in the validation set.

Contemporary trends in the utilization of second-line pharmacological therapies for type 2 diabetes in the United States and the United Kingdom.

AIM: To examine trends of second-line glucose-lowering therapies among patients with type 2 diabetes (T2D) initiating first-line metformin in the United States and the United Kingdom, overall and by subgroups of cardiovascular disease (CVD) and calendar time. METHODS: Using the US Optum Clinformatics and the UK Clinical Practice Research Datalink, we identified adults with T2D who initiated first-line metformin or sulphonylurea monotherapy, separately, from 2013 to 2019. Within both cohorts, we identified patterns of second-line medications through June 2021. We stratified patterns by CVD and calendar time to investigate the impact of rapidly evolving treatment guidelines. RESULTS: We identified 148 511 and 169 316 patients initiating treatment with metformin monotherapy in the United States and the United Kingdom, respectively. Throughout the study period, sulphonylureas and dipeptidyl peptidase-4 inhibitors were the most frequently initiated second-line medications in the United States (43.4% and 18.2%, respectively) and the United Kingdom (42.5% and 35.8%, respectively). After 2018, sodium-glucose co-transporter 2 inhibitors and glucagon-like peptide-1 receptor agonists were more commonly used as second-line agents in the United States and the United Kingdom, although these agents were not preferentially prescribed among patients with CVD. Initiation of first-line sulphonylureas was much less common, and most sulphonylurea initiators had metformin added as the second-line agent. CONCLUSIONS: This international cohort study shows that sulphonylureas remain the most common second-line medications prescribed following metformin in both the United States and the United Kingdom. Despite recommendations, the use of newer glucose-lowering therapies with cardiovascular benefits remains low.

Influenza Vaccination Uptake and Prognostic Factors among Health Professionals in Italy: Results from the Nationwide Surveillance PASSI 2015-2018.

(1) Influenza causes a significant health and socio-economic burden every year, and health personnel (HP) are at higher risk of exposure to respiratory pathogens than the general population. (2) The study's purpose was to describe and compare influenza vaccine uptake and its prognostic factors among Medical Doctors (MDs) and Non-Medical Health Personnel (NMHP) vs. Non-HP (NHP). We analyzed 2014-2018 data (n = 105,608) from the Italian Behavioral Risk Factor Surveillance System PASSI that, since 2008, has been collecting health-related information continuously in sampled adults. (3) MDs and NMHP represented, respectively, 1.1% and 4.6% of the sample. Among HP, 22.8% (CI 19.8-26.1%) of MDs and 8.5% (CI 7.5-9.5%) of NMHP reported to have been vaccinated vs. 6.3% (CI 6.1-6.5%) in NHP. This difference is confirmed in the three categories (MDs, NMHP, NHP), even more across age groups: in 18-34 yy, respectively, 9.9%, 4.4%, 3.4% vs. 28.4%, 13.9%, 10.6% in 50-64 yy. PASSI surveillance shows an increasing influenza vaccination uptake over time, especially among MDs (22.2% in 2014 vs. 30.5% in 2018). (4) Despite such an increase, especially among younger HP, influenza vaccination uptake is low. Even more under pandemic scenarios, these figures represent key information to address effective strategies for disease prevention and health promotion.

Emulation of Randomized Clinical Trials With Nonrandomized Database Analyses: Results of 32 Clinical Trials.

Importance: Nonrandomized studies using insurance claims databases can be analyzed to produce real-world evidence on the effectiveness of medical products. Given the lack of baseline randomization and measurement issues, concerns exist about whether such studies produce unbiased treatment effect estimates. Objective: To emulate the design of 30 completed and 2 ongoing randomized clinical trials (RCTs) of medications with database studies using observational analogues of the RCT design parameters (population, intervention, comparator, outcome, time [PICOT]) and to quantify agreement in RCT-database study pairs. Design, Setting, and Participants: New-user cohort studies with propensity score matching using 3 US claims databases (Optum Clinformatics, MarketScan, and Medicare). Inclusion-exclusion criteria for each database study were prespecified to emulate the corresponding RCT. RCTs were explicitly selected based on feasibility, including power, key confounders, and end points more likely to be emulated with real-world data. All 32 protocols were registered on ClinicalTrials.gov before conducting analyses. Emulations were conducted from 2017 through 2022. Exposures: Therapies for multiple clinical conditions were included. Main Outcomes and Measures: Database study emulations focused on the primary outcome of the corresponding RCT. Findings of database studies were compared with RCTs using predefined metrics, including Pearson correlation coefficients and binary metrics based on statistical significance agreement, estimate agreement, and standardized difference. Results: In these highly selected RCTs, the overall observed agreement between the RCT and the database emulation results was a Pearson correlation of 0.82 (95% CI, 0.64-0.91), with 75% meeting statistical significance, 66% estimate agreement, and 75% standardized difference agreement. In a post hoc analysis limited to 16 RCTs with closer emulation of trial design and measurements, concordance was higher (Pearson r, 0.93; 95% CI, 0.79-0.97; 94% meeting statistical significance, 88% estimate agreement, 88% standardized difference agreement). Weaker concordance occurred among 16 RCTs for which close emulation of certain design elements that define the research question (PICOT) with data from insurance claims was not possible (Pearson r, 0.53; 95% CI, 0.00-0.83; 56% meeting statistical significance, 50% estimate agreement, 69% standardized difference agreement). Conclusions and Relevance: Real-world evidence studies can reach similar conclusions as RCTs when design and measurements can be closely emulated, but this may be difficult to achieve. Concordance in results varied depending on the agreement metric. Emulation differences, chance, and residual confounding can contribute to divergence in results and are difficult to disentangle.

Comparing Effectiveness and Safety of SGLT2 Inhibitors vs DPP-4 Inhibitors in Patients With Type 2 Diabetes and Varying Baseline HbA1c Levels.

Importance: Sodium-glucose cotransporter 2 inhibitor (SGLT2i) therapy has been associated with cardiovascular benefits and a few adverse events; however, whether the comparative effectiveness and safety profiles vary with differences in baseline hemoglobin A1c (HbA1c) levels is unknown. Objective: To compare cardiovascular effectiveness and safety of treatment with SGLT2i vs dipeptidyl peptidase 4 inhibitor (DPP-4i) in adults with type 2 diabetes (T2D) (1) overall and (2) at varying baseline HbA1c levels. Design, Setting, and Participants: A new-user comparative effectiveness and safety research study was conducted among 144 614 commercially insured adults, initiating treatment with SGLT2i or DPP-4i and with a recorded T2D diagnosis at baseline and at least 1 HbA1c laboratory result recorded within 3 months before treatment initiation. Interventions: The intervention consisted of the initiation of treatment with SGLT2i or DPP-4i. Main Outcomes and Measures: Primary outcomes were a composite of myocardial infarction, stroke, or all-cause death (modified major adverse cardiovascular events [MACE]) and hospitalization for heart failure (HHF). Safety outcomes were hypovolemia, fractures, falls, genital infections, diabetic ketoacidosis (DKA), acute kidney injury (AKI), and lower-limb amputation. Incidence rate (IR) per 1000 person-years, hazard ratios (HR) and rate differences (RD) with their 95% CIs were estimated controlling for 128 covariates. Results: A total of 144 614 eligible adults (mean [SD] age, 62 [12.4] years; 54% male participants) with T2D initiating treatment with a SGLT2i (n = 60 523) or a DPP-4i (n = 84 091) were identified; 44 099 had an HbA1c baseline value of less than 7.5%, 52 986 between 7.5% and 9%, and 47 529 greater than 9%. Overall, 87 274 eligible patients were 1:1 propensity score-matched: 24 052 with HbA1c less than 7.5%; 32 290 with HbA1c between 7.5% and 9%; and 30 932 with HbA1c greater than 9% (to convert percentage of total hemoglobin to proportion of total hemoglobin, multiply by 0.01). The initiation of SGLT2i vs DPP-4i was associated with a reduction in the risk of modified MACE (IR per 1000 person-years 17.13 vs 20.18, respectively; HR, 0.85; 95% CI, 0.75-0.95; RD, -3.02; 95% CI, -5.23 to -0.80) and HHF (IR per 1000 person-years 3.68 vs 8.08, respectively; HR, 0.46; 95% CI, 0.35 to 0.57; RD -4.37; 95% CI, -5.62 to -3.12) over a mean follow-up of 8 months, with no evidence of treatment effect heterogeneity across the HbA1c levels. Treatment with SGLT2i showed an increased risk of genital infections and DKA and a reduced AKI risk compared with DPP-4i. Findings were consistent by HbA1c levels, except for a more pronounced risk of genital infections associated with SGLT2i for HbA1c levels of 7.5% to 9% (IR per 1000 person-years 68.5 vs 22.8, respectively; HR, 3.10; 95% CI, 2.68-3.58; RD, 46.22; 95% CI, 40.54-51.90). Conclusions and Relevance: In this comparative effectiveness and safety research study among adults with T2D, SGLT2i vs DPP-4i treatment initiators had a reduced risk of modified MACE and HHF, an increased risk of genital infections and DKA, and a lower risk of AKI, regardless of baseline HbA1c.

Safety of Sodium-Glucose Cotransporter-2 Inhibitors in Patients with CKD and Type 2 Diabetes: Population-Based US Cohort Study.

BACKGROUND: Limited information exists regarding the safety of sodium-glucose cotransporter-2 inhibitors (SGLT2i) in patients with CKD treated in routine care. We evaluated the safety of SGLT2i in patients with CKD and type 2 diabetes treated in US routine practice. METHODS: Using claims data from Medicare and two large US commercial databases (April 2013-December 2021), we included 96,128 adults with CKD stages 3-4 and type 2 diabetes who newly filled prescriptions for SGLT2i versus glucagon-like peptide-1 receptor agonists (GLP-1RA). Safety outcomes included diabetic ketoacidosis (DKA), lower limb amputations, nonvertebral fractures, genital infections, hypovolemia, AKI, hypoglycemia, and severe urinary tract infections (UTIs). Hazard ratios (HRs) and incidence rate differences per 1000 person-years were estimated after 1:1 propensity score matching, adjusted for >120 baseline characteristics. RESULTS: Compared with GLP-1RA, SGLT2i initiators had a higher risk of nonvertebral fractures (HR, 1.30; 95% confidence interval [CI], 1.03 to 1.65]; incidence rate difference, 2.13 [95% CI, 0.28 to 3.97]), lower limb amputations (HR, 1.65 [95% CI, 1.22 to 2.23]; incidence rate difference, 2.46 [95% CI, 1.00 to 3.92]), and genital infections (HR, 3.08 [95% CI, 2.73 to 3.48]; incidence rate difference, 41.26 [95% CI, 37.06 to 45.46]). Similar risks of DKA (HR, 1.07 [95% CI, 0.74 to 1.54]; incidence rate difference, 0.29 [95% CI, -0.89 to 1.46]), hypovolemia (HR, 0.99 [95% CI, 0.86 to 1.14]; incidence rate difference, 0.20 [95% CI, -2.85 to 3.25]), hypoglycemia (HR, 1.08 [95% CI, 0.92 to 1.26]; incidence rate difference, 1.46 [95% CI, -1.31 to 4.23]), and severe UTI (HR, 1.02 [95% CI, 0.87 to 1.19]; incidence rate difference, 0.35 [95% CI, -2.51 to 3.21]) were observed. SGLT2i had lower risk for AKI (HR, 0.93 [95% CI, 0.87 to 0.99]; incidence rate difference, -6.75 [95% CI, -13.69 to 0.20]). CONCLUSIONS: In US patients with CKD and type 2 diabetes receiving routine care, SGLT2i use was associated with higher risks of genital infections and potentially lower limb amputations and nonvertebral fractures.

Prospective validation of a dynamic prognostic model for identifying COVID-19 patients at high risk of rapid deterioration.

BACKGROUND: We sought to develop and prospectively validate a dynamic model that incorporates changes in biomarkers to predict rapid clinical deterioration in patients hospitalized for COVID-19. METHODS: We established a retrospective cohort of hospitalized patients aged ≥18 years with laboratory-confirmed COVID-19 using electronic health records (EHR) from a large integrated care delivery network in Massachusetts including >40 facilities from March to November 2020. A total of 71 factors, including time-varying vital signs and laboratory findings during hospitalization were screened. We used elastic net regression and tree-based scan statistics for variable selection to predict rapid deterioration, defined as progression by two levels of a published severity scale in the next 24 h. The development cohort included the first 70% of patients identified chronologically in calendar time; the latter 30% served as the validation cohort. A cut-off point was estimated to alert clinicians of high risk of imminent clinical deterioration. RESULTS: Overall, 3706 patients (2587 in the development and 1119 in the validation cohort) met the eligibility criteria with a median of 6 days of follow-up. Twenty-four variables were selected in the final model, including 16 dynamic changes of laboratory results or vital signs. Area under the ROC curve was 0.81 (95% CI, 0.79-0.82) in the development set and 0.74 (95% CI, 0.71-0.78) in the validation set. The model was well calibrated (slope = 0.84 and intercept = -0.07 on the calibration plot in the validation set). The estimated cut-off point, with a positive predictive value of 83%, was 0.78. CONCLUSIONS: Our prospectively validated dynamic prognostic model demonstrated temporal generalizability in a rapidly evolving pandemic and can be used to inform day-to-day treatment and resource allocation decisions based on dynamic changes in biophysiological factors.

Association of Sodium-Glucose Cotransporter-2 Inhibitors With Incident Atrial Fibrillation in Older Adults With Type 2 Diabetes.

Importance: Sodium-glucose cotransporter-2 inhibitors (SGLT-2is) have demonstrated many cardiovascular and kidney function benefits for patients with type 2 diabetes (T2D). However, the results of SGLT-2i use in primary prevention of atrial fibrillation (AF) were inconsistent in clinical trials, and incident AF was not a prespecified end point. Objective: To examine incident AF with initiation of an SGLT-2i compared with initiation of a dipeptidyl peptidase-4 inhibitor (DPP-4i) or a glucagonlike peptide-1 receptor agonist (GLP-1RA) among older adults (aged ≥66 years) with T2D in routine clinical practice. Design, Setting, and Participants: A population-based new-user cohort study included older adults with T2D who had no history of AF and were enrolled in Medicare fee-for-service from April 1, 2013, to December 31, 2018. Data analysis was performed from June 28 to December 1, 2021. Exposures: To control for potential confounding, new users of SGLT-2i were 1:1 propensity score (PS)-matched to new users of DPP-4is or GLP-1RAs in 2 pairwise comparisons based on 138 baseline covariates. Main Outcomes and Measures: The primary outcome was incident AF, defined as an inpatient diagnosis code for AF. Hazard ratios (HRs) and rate differences (RDs) per 1000 person-years, with their 95% CIs, were estimated in the PS-matched groups. Results: New users of SGLT-2is were 1:1 PS-matched to new users of a DPP-4i (n = 74 868) or GLP-1RA (n = 80 475). Overall, the mean (SD) age of study participants was 72 (5) years, and 165 984 were women (53.4%). The risk of incident AF was lower in the SGLT-2i group than the matched DPP-4i group (HR, 0.82; 95% CI, 0.76 to 0.89; RD, -3.7; 95% CI, -5.2 to -2.2 per 1000 person-years) or the matched GLP-1RA group (HR, 0.90; 95% CI, 0.83 to 0.98; RD, -1.8; 95% CI, -3.2 to -0.3 per 1000 person-years). Results were consistent across several sensitivity and subgroup analyses. Conclusions and Relevance: The findings of this study suggest that the initiation of an SGLT-2i was associated with a reduced risk of incident AF compared with a DPP-4i or GLP-1RA. The results may be helpful when weighing the potential risks and benefits of various glucose level-lowering agents in older adults with T2D.

Gastrointestinal prophylaxis for COVID-19: an illustration of severe bias arising from inappropriate comparators in observational studies.

OBJECTIVES: We aimed to use setting-appropriate comparisons to estimate the effects of different gastrointestinal (GI) prophylaxis pharmacotherapies for patients hospitalized with COVID-19 and setting-inappropriate comparisons to illustrate how improper design choices could result in biased results. STUDY DESIGN AND SETTING: We identified 3,804 hospitalized patients aged ≥ 18 years with COVID-19 from March to November 2020. We compared the effects of different gastroprotective agents on clinical improvement of COVID-19, as measured by a published severity scale. We used propensity score-based fine-stratification for confounding adjustment. Based on guidelines, we prespecified comparisons between agents with clinical equipoise and inappropriate comparisons of users vs. nonusers of GI prophylaxis in the intensive care unit (ICU). RESULTS: No benefit was detected when comparing oral famotidine to omeprazole in patients treated in the general ward or ICUs. We also found no associations when comparing intravenous famotidine to intravenous pantoprazole. For inappropriate comparisons of users vs. nonusers in the ICU, the probability of improvement was reduced by 32%-45% in famotidine users and 21%-48% in omeprazole or pantoprazole users. CONCLUSION: We found no evidence that GI prophylaxis improved outcomes for patients hospitalized with COVID-19 in setting-appropriate comparisons. An improper comparator choice can lead to spurious associations in critically ill patients.

Cardiovascular Risks of Hydroxychloroquine vs Methotrexate in Patients With Rheumatoid Arthritis.

BACKGROUND: Hydroxychloroquine is often used as a first-line treatment of rheumatoid arthritis despite limited evidence on its cardiovascular risk. OBJECTIVES: We conducted a cardiovascular safety evaluation comparing hydroxychloroquine to methotrexate among patients with rheumatoid arthritis. METHODS: Using Medicare data (2008-2016), we identified 54,462 propensity score-matched patients with rheumatoid arthritis, aged ≥65 years, who initiated hydroxychloroquine or methotrexate. Primary outcomes were sudden cardiac arrest or ventricular arrythmia (SCA/VA) and major adverse cardiovascular event (MACE). Secondary outcomes were cardiovascular mortality, all-cause mortality, myocardial infarction, stroke, and hospitalized heart failure (HF). We also examined treatment effect modification by history of HF. RESULTS: Hydroxychloroquine was not associated with risk of SCA/VA (HR: 1.03; 95% CI: 0.79-1.35) or MACE (HR: 1.07; 95% CI: 0.97-1.18) compared with methotrexate. In patients with history of HF, hydroxychloroquine initiators had a higher risk of MACE (HR: 1.30; 95% CI: 1.08-1.56), cardiovascular mortality (HR: 1.34; 95% CI: 1.06-1.70), all-cause mortality (HR: 1.22; 95% CI: 1.04-1.43), myocardial infarction (HR: 1.74; 95% CI: 1.25-2.42), and hospitalized HF (HR: 1.29; 95% CI: 1.07-1.54) compared to methotrexate initiators. Cardiovascular risks were not different in patients without history of HF except for an increased hospitalized HF risk (HR: 1.57; 95% CI: 1.30-1.90) among hydroxychloroquine initiators. CONCLUSIONS: In older patients with rheumatoid arthritis, hydroxychloroquine and methotrexate showed similar SCA/VA and MACE risks; however, hydroxychloroquine initiators with history of HF had higher risks of MACE, cardiovascular mortality, all-cause mortality, and myocardial infarction. An increased hospitalized HF risk was observed among hydroxychloroquine initiators regardless of an HF history.

Characteristics of Clinical Trials Evaluating Biosimilars in the Treatment of Cancer: A Systematic Review and Meta-analysis.

IMPORTANCE: Biologics account for almost half of US drug spending but may be subject to competitive pricing pressures by US Food and Drug Administration-approved biosimilars. The extent of the preapproval clinical testing that is needed and how these biosimilars compare with the originator biologic products remain critical issues in establishing a vibrant biosimilar market. OBJECTIVES: To analyze the design of cancer biosimilar efficacy studies compared with the reference drug pivotal trials and provide summary risk ratio estimates for each cancer type drug subgroup. DATA SOURCES: A systematic search was performed of articles and abstracts published using Embase, PubMed/MEDLINE, and ClinicalTrials.gov, last updated April 18, 2021. STUDY SELECTION: All studies or abstracts in English comparing a disease-modifying cancer biologic and its biosimilar and reporting efficacy or surrogate efficacy results were included. DATA EXTRACTION AND SYNTHESIS: Outcome estimates and study characteristics were extracted from each study. Among biosimilar efficacy studies, random-effects meta-analyses were performed for each cancer type molecule outcome subgroup, calculating pooled relative estimates and 95% CIs. MAIN OUTCOMES AND MEASURES: Study characteristics, such as population size, blinding, and randomization, were compared between biosimilar trials and those of reference drugs. Risk ratio estimates for relative change to surrogate measures (eg, progression-free survival) were collected for biosimilars and their reference products. RESULTS: A total of 31 cancer biosimilar studies of 3 reference products involving 12 310 patients were included. In all 7 subgroups, the biosimilars analyzed were indistinguishable from their reference drug on surrogate efficacy. Six reference drug trials were included, involving 1811 patients. On average, biosimilar studies involved more patients than reference drug trials (mean number of patients, 397 vs 302), were more likely to be randomized clinical trials rather than single-group or observational studies (100% [31 of 31] vs 50% [3 of 6]), and were more likely to be double blind rather than open label (84% [26 of 31] vs 17% [1 of 6]). CONCLUSIONS AND RELEVANCE: This systematic review and meta-analysis found that the biosimilars for the cancer drugs in this sample were subjected to rigorous clinical evaluations, and the results were statistically indistinguishable from those of original products across drugs, cancer types, and outcome measures.

Prevalence of Avoidable and Bias-Inflicting Methodological Pitfalls in Real-World Studies of Medication Safety and Effectiveness.

Many real-word evidence (RWE) studies that utilize existing healthcare data to evaluate treatment effects incur substantial but avoidable bias from methodologically flawed study design; however, the extent of preventable methodological pitfalls in current RWE is unknown. To characterize the prevalence of avoidable methodological pitfalls with potential for bias in published claims-based studies of medication safety or effectiveness, we conducted an English-language search of PubMed for articles published from January 1, 2010 to May 20, 2019 and randomly selected 75 studies (10 case-control and 65 cohort studies) that evaluated safety or effectiveness of cardiovascular, diabetes, or osteoporosis medications using US health insurance claims. General and methodological study characteristics were extracted independently by two reviewers, and potential for bias was assessed across nine bias domains. Nearly all studies (95%) had at least one avoidable methodological issue known to incur bias, and 81% had potentially at least one of the four issues considered major due to their potential to undermine study validity: time-related bias (57%), potential for depletion of outcome-susceptible individuals (44%), inappropriate adjustment for postbaseline variables (41%), or potential for reverse causation (39%). The median number of major issues per study was 2 (interquartile range (IQR), 1-3) and was lower in cohort studies with a new-user, active-comparator design (median 1, IQR 0-1) than in cohort studies of prevalent users with a nonuser comparator (median 3, IQR 3-4). Recognizing and avoiding known methodological study design pitfalls could substantially improve the utility of RWE and confidence in its validity.

How well can we assess the validity of non-randomised studies of medications? A systematic review of assessment tools.

OBJECTIVE: To determine whether assessment tools for non-randomised studies (NRS) address critical elements that influence the validity of NRS findings for comparative safety and effectiveness of medications. DESIGN: Systematic review and Delphi survey. DATA SOURCES: We searched PubMed, Embase, Google, bibliographies of reviews and websites of influential organisations from inception to November 2019. In parallel, we conducted a Delphi survey among the International Society for Pharmacoepidemiology Comparative Effectiveness Research Special Interest Group to identify key methodological challenges for NRS of medications. We created a framework consisting of the reported methodological challenges to evaluate the selected NRS tools. STUDY SELECTION: Checklists or scales assessing NRS. DATA EXTRACTION: Two reviewers extracted general information and content data related to the prespecified framework. RESULTS: Of 44 tools reviewed, 48% (n=21) assess multiple NRS designs, while other tools specifically addressed case-control (n=12, 27%) or cohort studies (n=11, 25%) only. Response rate to the Delphi survey was 73% (35 out of 48 content experts), and a consensus was reached in only two rounds. Most tools evaluated methods for selecting study participants (n=43, 98%), although only one addressed selection bias due to depletion of susceptibles (2%). Many tools addressed the measurement of exposure and outcome (n=40, 91%), and measurement and control for confounders (n=40, 91%). Most tools have at least one item/question on design-specific sources of bias (n=40, 91%), but only a few investigate reverse causation (n=8, 18%), detection bias (n=4, 9%), time-related bias (n=3, 7%), lack of new-user design (n=2, 5%) or active comparator design (n=0). Few tools address the appropriateness of statistical analyses (n=15, 34%), methods for assessing internal (n=15, 34%) or external validity (n=11, 25%) and statistical uncertainty in the findings (n=21, 48%). None of the reviewed tools investigated all the methodological domains and subdomains. CONCLUSIONS: The acknowledgement of major design-specific sources of bias (eg, lack of new-user design, lack of active comparator design, time-related bias, depletion of susceptibles, reverse causation) and statistical assessment of internal and external validity is currently not sufficiently addressed in most of the existing tools. These critical elements should be integrated to systematically investigate the validity of NRS on comparative safety and effectiveness of medications. SYSTEMATIC REVIEW PROTOCOL AND REGISTRATION: https://osf.io/es65q.

A correlation analysis to assess event-free survival as a trial-level surrogate for overall survival in early breast cancer.

BACKGROUND: Event-free survival (EFS) has been listed on the FDA Table of Surrogate Endpoints as a surrogate measure that can be considered for accelerated or traditional approval in breast cancer. However, no studies have evaluated the correlation between the treatment effects on EFS and treatment effects on overall survival (OS). METHODS: We performed a systematic search of the literature until May 2020 according to the PRISMA guideline for all published randomized controlled trials (RCTs) in early breast cancer in the neoadjuvant setting. Data on EFS and OS, including the hazard ratio (HR) and 95% confidence intervals (CI), were extracted from each study and the association between the trial-level EFS HR and the trial-level OS HR was estimated using a linear mixed-effects model on the log scale. FINDINGS: Of the 7 RCTs (N = 2211) included in the analysis, 5 included patients with HER2 positive tumor type. The estimated linear association between log HR EFS and log HR OS indicated a positive slope ( ß  = 0.58 [95% CI: -0.32-1.48]) and the coefficient of determination confirmed a moderate trial-level association between log HRs for OS and EFS (R² 0.76 [95% CI 0.34-1.00], but with wide confidence intervals. INTERPRETATION: Treatment effects in EFS are moderately correlated with treatment effects in OS in early breast cancer in the neoadjuvant setting, but the association was not significant. Thus, there is currently insufficient evidence to support EFS for use as a surrogate endpoint for traditional approval, although it may be considered for accelerated approval. FUNDING: Arnold Ventures.

Pharmacotherapy for Hospitalized Patients with COVID-19: Treatment Patterns by Disease Severity.

BACKGROUND: Treatment decisions for Coronavirus Disease 2019 (COVID-19) depend on disease severity, but the prescribing pattern by severity and drivers of therapeutic choices remain unclear. OBJECTIVES: The objectives of the study were to evaluate pharmacological treatment patterns by COVID-19 severity and identify the determinants of prescribing for COVID-19. METHODS: Using electronic health record data from a large Massachusetts-based healthcare system, we identified all patients aged ≥ 18 years hospitalized with laboratory-confirmed COVID-19 from 1 March to 24 May, 2020. We defined five levels of COVID-19 severity at hospital admission: (1) hospitalized but not requiring supplemental oxygen; (2-4) hospitalized and requiring oxygen ≤ 2, 3-4, and ≥ 5 L per minute, respectively; and (5) intubated or admitted to an intensive care unit. We assessed the medications used to treat COVID-19 or as supportive care during hospitalization. RESULTS: Among 2821 patients hospitalized for COVID-19, we found inpatient mortality increased by severity from 5% for level 1 to 23% for level 5. As compared to patients with severity level 1, those with severity level 5 were 3.53 times (95% confidence interval 2.73-4.57) more likely to receive a medication used to treat COVID-19. Other predictors of treatment were fever, low oxygen saturation, presence of co-morbidities, and elevated inflammatory biomarkers. The use of most COVID-19 relevant medications has dropped substantially while the use of remdesivir and therapeutic anticoagulants has increased over the study period. CONCLUSIONS: Careful consideration of disease severity and other determinants of COVID-19 drug use is necessary for appropriate conduct and interpretation of non-randomized studies evaluating outcomes of COVID-19 treatments.

Heterogeneity of antidiabetic treatment effect on the risk of major adverse cardiovascular events in type 2 diabetes: a systematic review and meta-analysis.

BACKGROUND: We explored whether clinically relevant baseline characteristics of patients with type 2 diabetes can modify the effect of glucagon-like peptide-1 receptor agonists (GLP-1 RA) or sodium-glucose cotransporter-2 inhibitors (SGLT-2i) on the risk of major adverse cardiovascular events (MACE). METHODS: We investigated Medline and EMBASE through June 2019. We included randomized clinical trials reporting the effect of GLP-1 RA or SGLT-2i on MACE in subgroups of patients with type 2 diabetes, identified through key baseline factors: established cardiovascular disease; heart failure; chronic kidney disease; uncontrolled diabetes; duration of diabetes; hypertension; obesity; age; gender and race. Hazard ratios (HRs) and 95% confidence intervals (CIs) from trials were meta-analyzed using random-effects models. RESULTS: Ten trials enrolling 89,790 patients were included in the analyses. Subgroup meta-analyses showed a 14% risk reduction of MACE in patients with established cardiovascular disease [GLP1-RA: HR, 0.86 (95% CI, 0.80-0.93); SGLT-2i: 0.86 (0.80-0.93)], and no effect in at-risk patients without history of cardiovascular events [GLP1-RA: 0.94 (0.82-1.07); SGLT-2i: 1.00 (0.87-1.16)]. We observed a trend toward larger treatment benefits with SGLT-2i among patients with chronic kidney disease [0.82 (0.69-0.97)], and patients with uncontrolled diabetes for both GLP1-RA or SGLT-2i [GLP1-RA: 0.82 (0.71-0.95); SGLT-2i: 0.84 (0.75-0.95)]. Uncontrolled hypertension, obesity, gender, age and race did not appear to modify the effect of these drugs. CONCLUSIONS: In this exploratory analysis, history of cardiovascular disease appeared to modify the treatment effect of SGLT2i or GLP1-RA on MACE. Chronic kidney disease and uncontrolled diabetes should be further investigated as potential effect modifiers.

Genomics knowledge and attitudes among European public health professionals: Results of a cross-sectional survey.

BACKGROUND: The international public health (PH) community is debating the opportunity to incorporate genomic technologies into PH practice. A survey was conducted to assess attitudes of the European Public Health Association (EUPHA) members towards their role in the implementation of public health genomics (PHG), and their knowledge and attitudes towards genetic testing and the delivery of genetic services. METHODS: EUPHA members were invited via monthly newsletter and e-mail to take part in an online survey from February 2017 to January 2018. A descriptive analysis of knowledge and attitudes was conducted, along with a univariate and multivariate analysis of their determinants. RESULTS: Five hundred and two people completed the questionnaire, 17.9% were involved in PHG activities. Only 28.9% correctly identified all medical conditions for which there is (or not) evidence for implementing genetic testing; over 60% thought that investing in genomics may divert economic resources from social and environmental determinants of health. The majority agreed that PH professionals may play different roles in incorporating genomics into their activities. Better knowledge was associated with positive attitudes towards the use of genetic testing and the delivery of genetic services in PH (OR = 1.48; 95% CI 1.01-2.18). CONCLUSIONS: Our study revealed quite positive attitudes, but also a need to increase awareness on genomics among European PH professionals. Those directly involved in PHG activities tend to have a more positive attitude and better knowledge; however, gaps are also evident in this group, suggesting the need to harmonize practice and encourage greater exchange of knowledge among professionals.

Response Rates and Durations of Response for Biomarker-Based Cancer Drugs in Nonrandomized Versus Randomized Trials.

BACKGROUND: Many new targeted cancer drugs have received FDA approval based on durable responses in nonrandomized controlled trials (non-RCTs). The goal of this study was to evaluate whether the response rates (RRs) and durations of response (DoRs) of targeted cancer drugs observed in non-RCTs are consistent when these drugs are tested in RCTs. METHODS: We used the FDA's Table of Pharmacogenomic Biomarkers in Drug Labeling to identify cancer drugs that were approved based on changes in biomarker endpoints through December 2017. We then identified the non-RCTs and RCTs for these drugs for the given indications and extracted the RRs and DoRs. We compared the RRs and median DoR in non-RCTs versus RCTs using the ratio of RRs and the ratio of DoRs, defined as the RRs (or DoRs) in non-RCTs divided by the RRs (or DoRs) in RCTs. The ratio of RRs or DoRs was pooled across the trial pairs using random-effects meta-analysis. RESULTS: Of the 21 drug-indication pairs selected, both non-RCTs and RCTs were available for 19. The RRs and DoRs in non-RCTs were greater than those in RCTs in 63% and 87% of cases, respectively. The pooled ratio of RRs was 1.06 (95% CI, 0.95-1.20), and the pooled ratio of DoRs was 1.17 (95% CI, 1.03-1.33). RRs and DoRs derived from non-RCTs were also poor surrogates for overall survival derived from RCTs. CONCLUSIONS: The RRs were not different between non-RCTs and RCTs of cancer drugs approved based on changes to a biomarker, but the DoRs in non-RCTs were significantly higher than in RCTs. Caution must be exercised when approving or prescribing targeted drugs based on data on durable responses derived from non-RCTs, because the responses could be overestimates and poor predictors of survival benefit.