Real-World Trends in the Evaluation of Medical Products.

There is a compelling need to evaluate the real-world health effects of medical products outside of tightly controlled preapproval clinical trials. This is done through pharmacoepidemiology, which is the study of the health effects of medical products (including drugs, biologicals, and medical devices and diagnostics) in populations, often using nonrandomized designs. Recent developments in pharmacoepidemiology span changes in the focus of research questions, research designs, data used, and statistical analysis methods. Developments in these areas are thought to improve the value of the evidence produced by such studies, and are prompting greater use of real-world evidence to inform clinical, regulatory, and reimbursement decisions.

Comparative Effectiveness of Famotidine in Hospitalized COVID-19 Patients.

INTRODUCTION: Famotidine has been posited as a potential treatment for coronavirus disease 2019 (COVID-19). We compared the incidence of COVID-19 outcomes (i.e., death and death or intensive services use) among hospitalized famotidine users vs proton pump inhibitors (PPIs) users, hydroxychloroquine users, or famotidine nonusers separately. METHODS: We constructed a retrospective cohort study using data from COVID-19 Premier Hospital electronic health records. The study population was COVID-19 hospitalized patients aged 18 years or older. Famotidine, PPI, and hydroxychloroquine exposure groups were defined as patients dispensed any medication containing 1 of the 3 drugs on the day of admission. The famotidine nonuser group was derived from the same source population with no history of exposure to any drug with famotidine as an active ingredient before or on the day of admission. Time at risk was defined based on the intention-to-treat principle starting 1 day after admission to 30 days after admission. For each study comparison group, we fit a propensity score model through large-scale regularized logistic regression. The outcome was modeled using a survival model. RESULTS: We identified 2,193 users of PPI, 5,950 users of the hydroxychloroquine, 1,816 users of famotidine, and 26,820 nonfamotidine users. After propensity score stratification, the hazard ratios (HRs) for death were as follows: famotidine vs no famotidine HR 1.03 (0.89-1.18), vs PPIs: HR 1.14 (0.94-1.39), and vs hydroxychloroquine: 1.03 (0.85-1.24). Similar results were observed for the risk of death or intensive services use. DISCUSSION: We found no evidence of a reduced risk of COVID-19 outcomes among hospitalized COVID-19 patients who used famotidine compared with those who did not or compared with PPI or hydroxychloroquine users.

Quantifying bias in epidemiologic studies evaluating the association between acetaminophen use and cancer.

Many observational studies explore the association between acetaminophen and cancer, but known limitations such as vulnerability to channeling, protopathic bias, and uncontrolled confounding hamper the interpretability of results. To help understand the potential magnitude of bias, we identify key design choices in these observational studies and specify 10 study design variants that represent different combinations of these design choices. We evaluate these variants by applying them to 37 negative controls - outcome presumed not to be caused by acetaminophen - as well as 4 cancer outcomes in the Clinical Practice Research Datalink (CPRD) database. The estimated odds and hazards ratios for the negative controls show substantial bias in the evaluated design variants, with far fewer of the 95% confidence intervals containing 1 than the nominal 95% expected for negative controls. The effect-size estimates for the cancer outcomes are comparable to those observed for the negative controls. A comparison of exposed and unexposed reveals many differences at baseline for which most studies do not correct. We observe that the design choices made in many of the published observational studies can lead to substantial bias. Thus, caution in the interpretation of published studies of acetaminophen and cancer is recommended.

A systematic assessment of the epidemiologic literature regarding an association between acetaminophen exposure and cancer.

Introduced in the 1950s, acetaminophen is one of the most widely used antipyretics and analgesics worldwide. In 1999, the International Agency for Research on Cancer (IARC) reviewed the epidemiologic studies of acetaminophen and the data were judged to be "inadequate" to conclude that it is carcinogenic. In 2019 the California Office of Environmental Health Hazard Assessment initiated a review process on the carcinogenic hazard potential of acetaminophen. To inform this review process, the authors performed a comprehensive literature search and identified 136 epidemiologic studies, which for most cancer types suggest no alteration in risk associated with acetaminophen use. For 3 cancer types, renal cell, liver, and some forms of lymphohematopoietic, some studies suggest an increased risk; however, multiple factors unique to acetaminophen need to be considered to determine if these results are real and clinically meaningful. The objective of this publication is to analyze the results of these epidemiologic studies using a framework that accounts for the inherent challenge of evaluating acetaminophen, including, broad population-wide use in multiple disease states, challenges with exposure measurement, protopathic bias, channeling bias, and recall bias. When evaluated using this framework, the data do not support a causal association between acetaminophen use and cancer.

Methods for external control groups for single arm trials or long-term uncontrolled extensions to randomized clinical trials.

PURPOSE: Clinical trials compare outcomes among patients receiving study treatment with comparators drawn from the same source. These internal controls are missing in single arm trials and from long-term extensions (LTE) of trials including only the treatment arm. An external control group derived from a different setting is then required to assess safety or effectiveness. METHODS: We present examples of external control groups that demonstrate some of the issues that arise and make recommendations to address them through careful assessment of the data source fitness for use, design, and analysis steps. RESULTS: Inclusion and exclusion criteria and context that produce a trial population may result in trial patients with different clinical characteristics than are present in an external comparison group. If these differences affect the risk of outcomes, then a comparison of outcome occurrence will be confounded. Further, patients who continue into LTE may differ from those initially entering the trial due to treatment effects. Application of appropriate methods is needed to make valid inferences when such treatment or selection effects are present. Outcome measures in a trial may be ascertained and defined differently from what can be obtained in an external comparison group. Differences in sensitivity and specificity for identification or measurement of study outcomes leads to information bias that can also invalidate inferences. CONCLUSION: This review concentrates on threats to the valid use of external control groups both in the scenarios of single arm trials and LTE of randomized controlled trials, along with methodological approaches to mitigate them.

Diabetic ketoacidosis in patients with type 2 diabetes treated with sodium glucose co-transporter 2 inhibitors versus other antihyperglycemic agents: An observational study of four US administrative claims databases.

PURPOSE: To compare the incidence of diabetic ketoacidosis (DKA) among patients with type 2 diabetes mellitus (T2DM) who were new users of sodium glucose co-transporter 2 inhibitors (SGLT2i) versus other classes of antihyperglycemic agents (AHAs). METHODS: Patients were identified from four large US claims databases using broad (all T2DM patients) and narrow (intended to exclude patients with type 1 diabetes or secondary diabetes misclassified as T2DM) definitions of T2DM. New users of SGLT2i and seven groups of comparator AHAs were matched (1:1) on exposure propensity scores to adjust for imbalances in baseline covariates. Cox proportional hazards regression models, conditioned on propensity score-matched pairs, were used to estimate hazard ratios (HRs) of DKA for new users of SGLT2i versus other AHAs. When I2 <40%, a combined HR across the four databases was estimated. RESULTS: Using the broad definition of T2DM, new users of SGLT2i had an increased risk of DKA versus sulfonylureas (HR [95% CI]: 1.53 [1.31-1.79]), DPP-4i (1.28 [1.11-1.47]), GLP-1 receptor agonists (1.34 [1.12-1.60]), metformin (1.31 [1.11-1.54]), and insulinotropic AHAs (1.38 [1.15-1.66]). Using the narrow definition of T2DM, new users of SGLT2i had an increased risk of DKA versus sulfonylureas (1.43 [1.01-2.01]). New users of SGLT2i had a lower risk of DKA versus insulin and a similar risk as thiazolidinediones, regardless of T2DM definition. CONCLUSIONS: Increased risk of DKA was observed for new users of SGLT2i versus several non-SGLT2i AHAs when T2DM was defined broadly. When T2DM was defined narrowly to exclude possible misclassified patients, an increased risk of DKA with SGLT2i was observed compared with sulfonylureas.

Risk of lower extremity amputations in people with type 2 diabetes mellitus treated with sodium-glucose co-transporter-2 inhibitors in the USA: A retrospective cohort study.

AIMS: To examine the incidence of amputation in patients with type 2 diabetes mellitus (T2DM) treated with sodium glucose co-transporter 2 (SGLT2) inhibitors overall, and canagliflozin specifically, compared with non-SGLT2 inhibitor antihyperglycaemic agents (AHAs). MATERIALS AND METHODS: Patients with T2DM newly exposed to SGLT2 inhibitors or non-SGLT2 inhibitor AHAs were identified using the Truven MarketScan database. The incidence of below-knee lower extremity (BKLE) amputation was calculated for patients treated with SGLT2 inhibitors, canagliflozin, or non-SGLT2 inhibitor AHAs. Patients newly exposed to canagliflozin and non-SGLT2 inhibitor AHAs were matched 1:1 on propensity scores, and a Cox proportional hazards model was used for comparative analysis. Negative controls (outcomes not believed to be associated with any AHA) were used to calibrate P values. RESULTS: Between April 1, 2013 and October 31, 2016, 118 018 new users of SGLT2 inhibitors, including 73 024 of canagliflozin, and 226 623 new users of non-SGLT2 inhibitor AHAs were identified. The crude incidence rates of BKLE amputation were 1.22, 1.26 and 1.87 events per 1000 person-years with SGLT2 inhibitors, canagliflozin and non-SGLT2 inhibitor AHAs, respectively. For the comparative analysis, 63 845 new users of canagliflozin were matched with 63 845 new users of non-SGLT2 inhibitor AHAs, resulting in well-balanced baseline covariates. The incidence rates of BKLE amputation were 1.18 and 1.12 events per 1000 person-years with canagliflozin and non-SGLT2 inhibitor AHAs, respectively; the hazard ratio was 0.98 (95% confidence interval 0.68-1.41; P = .92, calibrated P = .95). CONCLUSIONS: This real-world study observed no evidence of increased risk of BKLE amputation for new users of canagliflozin compared with non-SGLT2 inhibitor AHAs in a broad population of patients with T2DM.

Comparative effectiveness of canagliflozin, SGLT2 inhibitors and non-SGLT2 inhibitors on the risk of hospitalization for heart failure and amputation in patients with type 2 diabetes mellitus: A real-world meta-analysis of 4 observational databases (OBSERVE-4D).

AIMS: Sodium glucose co-transporter 2 inhibitors (SGLT2i) are indicated for treatment of type 2 diabetes mellitus (T2DM); some SGLT2i have reported cardiovascular benefit, and some have reported risk of below-knee lower extremity (BKLE) amputation. This study examined the real-world comparative effectiveness within the SGLT2i class and compared with non-SGLT2i antihyperglycaemic agents. MATERIALS AND METHODS: Data from 4 large US administrative claims databases were used to characterize risk and provide population-level estimates of canagliflozin's effects on hospitalization for heart failure (HHF) and BKLE amputation vs other SGLT2i and non-SGLT2i in T2DM patients. Comparative analyses using a propensity score-adjusted new-user cohort design examined relative hazards of outcomes across all new users and a subpopulation with established cardiovascular disease. RESULTS: Across the 4 databases (142 800 new users of canagliflozin, 110 897 new users of other SGLT2i, 460 885 new users of non-SGLT2i), the meta-analytic hazard ratio estimate for HHF with canagliflozin vs non-SGLT2i was 0.39 (95% CI, 0.26-0.60) in the on-treatment analysis. The estimate for BKLE amputation with canagliflozin vs non-SGLT2i was 0.75 (95% CI, 0.40-1.41) in the on-treatment analysis and 1.01 (95% CI, 0.93-1.10) in the intent-to-treat analysis. Effects in the subpopulation with established cardiovascular disease were similar for both outcomes. No consistent differences were observed between canagliflozin and other SGLT2i. CONCLUSIONS: In this large comprehensive analysis, canagliflozin and other SGLT2i demonstrated HHF benefits consistent with clinical trial data, but showed no increased risk of BKLE amputation vs non-SGLT2i. HHF and BKLE amputation results were similar in the subpopulation with established cardiovascular disease. This study helps further characterize the potential benefits and harms of SGLT2i in routine clinical practice to complement evidence from clinical trials and prior observational studies.

Association between complete response and outcomes in transplant-eligible myeloma patients in the era of novel agents.

OBJECTIVES: Achieving complete response (CR) has been linked to improved progression-free (PFS) and overall (OS) survival in myeloma. A meta-analysis was conducted to investigate whether this holds true in the era of novel agents (bortezomib, lenalidomide, thalidomide). METHODS: A total of 24 studies in newly diagnosed patients undergoing autologous stem cell transplantation (ASCT) that reported associations between responses and long-term outcomes (PFS/OS rates post-ASCT by response, or hazard ratios with 95% confidence intervals from Cox models) were identified and analyzed. RESULTS: Achievement of CR vs.

Quality of Meta-Analyses for Randomized Trials in the Field of Hypertension: an Updated and Improved Systematic Review.

Publications of hypertension-related meta-analyses (MAs) have increased exponentially in the past 25 years and now average 8/month. Theoretically, this is facilitating evidence-based management of patients. However, some practitioners and authors of guidelines have questioned the quality of published MAs. By extending a prior review, we have assessed the quality of 212 hypertension-related meta-analyses over 5 years based on systematically searching three computerized libraries. Seventeen criteria grouped into four domains of quality yielded the following results: (1) Assessment of trial quality was accomplished in 89% of MAs, and 38% analyzed trials in subgroups of trial quality where appropriate. (2) All three measures of heterogeneity (I 2, tau, and P for heterogeneity) were reported in 36%, reflecting the failure to report tau, the standard deviation of the main effect. (3) Publication bias was assessed in 75%, and 43% of MAs used a statistical test for publication bias. (4) Regarding transparency, 9 to 31% of MAs reported problems in the previous three domains in the article's abstract. Journal impact factor reporting the MAs declined significantly over 5 years. The percent with criteria of quality in a MA was modestly correlated with journal impact factor (R 2 = 0.05, P = 0.001). False-positive results from inappropriate application of the DerSimonian-Laird model affected 25% of articles, which reported these false positives in the article's abstract in 72%. No more than 25% of MAs had 67% or more of the criteria of quality. In conclusion, skepticism of hypertension-related MAs is justified, but their quality can be readily corrected.

Changes in the use of erythropoiesis-stimulating agents (ESAs) and red blood cell transfusion in patients with cancer amidst regulatory and reimbursement changes.

PURPOSE: Evaluate changes in use of erythropoiesis-stimulating agents (ESAs) and red blood cell transfusion in cancer patients receiving myelosuppressive chemotherapy following regulatory and reimbursement actions. METHODS: Calendar year patient cohorts (2005-2013) with breast, colorectal, lung, multiple myeloma, non-Hodgkin lymphoma, ovarian, or prostate cancer and receiving myelosuppressive chemotherapy were identified within the Marketscan database. Incidence of ESA treatment and transfusion were estimated in each year, as was median number of ESA administrations. Clinical characteristics associated with ESA administration and transfusions were evaluated by using multivariable logistic regression. Additionally, annual new ESA user cohorts within the Oncology Services Comprehensive Electronic Records database (2011-2014) were examined to assess hemoglobin levels at ESA initiation. RESULTS: Across all tumor types, ESA use decreased substantially (breast cancer: 53.7 to 3.2%; lung cancer: 66.0 to 13.3%, non-Hodgkin lymphoma: 39.8 to 3.8%), transfusion use increased (2 to 5.5%, 5.5 to 18.2%, and 4.5 to 9.1%, respectively), and median number of ESA administrations declined. Across all tumor types, proportion of patients initiating an ESA with hemoglobin >10 g/dL was <10% from 2011 onward. In recent years, cancer patients who are older, female, and have chronic kidney disease or moderate or severe liver disease were most likely to receive ESAs. CONCLUSION: Subsequent to important regulatory and reimbursement ESA-related actions, total ESA exposure among cancer patients receiving myelosuppressive chemotherapy declined substantially. Today, fewer patients receive ESA therapy, and among those treated, more are initiated at hemoglobin levels <10 g/dL and are exposed for a shorter duration, consistent with current product labeling.

Baseline characteristics and treatment-emergent risk factors associated with cerebrovascular event and death with risperidone in dementia patients.

BACKGROUND: Use of antipsychotics to treat behavioural symptoms of dementia has been associated with increased risks of mortality and stroke. Little is known about individual patient characteristics that might be associated with bad or good outcomes. AIMS: We examined the risperidone clinical trial data to look for individual patient characteristics associated with these adverse outcomes. METHOD: Data from all double-blind randomised controlled trials of risperidone in dementia patients (risperidone n = 1009, placebo n = 712) were included. Associations between characteristics and outcome were analysed based on crude incidences and exposure-adjusted incidence rates, and by time-to-event analyses using Cox proportional hazards regression. Interactions between treatment (risperidone or placebo) and characteristic were analysed with a Cox proportional hazards regression model with main effects for treatment and characteristic in addition to the interaction term. RESULTS: Baseline complications of depression (treatment by risk factor interaction on cerebrovascular adverse event (CVAE) hazard ratio (HR): P = 0.025) and delusions (P = 0.043) were associated with a lower relative risk of CVAE in risperidone-treated patients (HR = 1.47 and 0.54, respectively) compared to not having the complication (HR = 5.88 and 4.16). For mortality, the only significant baseline predictor in patients treated with risperidone was depression, which was associated with a lower relative risk (P<0.001). The relative risk of mortality was increased in risperidone patients treated with anti-inflammatory medications (P = 0.021). CONCLUSIONS: Only anti-inflammatory medications increased mortality risk with risperidone. The reduced risks of CVAE in patients with comorbid depression and delusions, and of mortality with depression, may have clinical implications when weighing the benefits and risks of treatment with risperidone in patients with dementia.

Causal inference methods to assess safety upper bounds in randomized trials with noncompliance.

BACKGROUND: Premature discontinuation and other forms of noncompliance with treatment assignment can complicate causal inference of treatment effects in randomized trials. The intent-to-treat analysis gives unbiased estimates for causal effects of treatment assignment on outcome, but may understate potential benefit or harm of actual treatment. The corresponding upper confidence limit can also be underestimated. PURPOSE: To compare estimates of the hazard ratio and upper bound of the two-sided 95% confidence interval from causal inference methods that account for noncompliance with those from the intent-to-treat analysis. METHODS: We used simulations with parameters chosen to reflect cardiovascular safety trials of diabetes drugs, with a focus on upper bound estimates relative to 1.3, based on regulatory guidelines. A total of 1000 simulations were run under each parameter combination for a hypothetical trial of 10,000 total subjects randomly assigned to active treatment or control at 1:1 ratio. Noncompliance was considered in the form of treatment discontinuation and cross-over at specified proportions, with an assumed true hazard ratio of 0.9, 1, and 1.3, respectively. Various levels of risk associated with being a non-complier (independent of treatment status) were evaluated. Hazard ratio and upper bound estimates from causal survival analysis and intent-to-treat were obtained from each simulation and summarized under each parameter setting. RESULTS: Causal analysis estimated the true hazard ratio with little bias in almost all settings examined. Intent-to-treat was unbiased only when the true hazard ratio = 1; otherwise it underestimated both benefit and harm. When upper bound estimates from intent-to-treat were ≥1.3, corresponding estimates from causal analysis were also ≥1.3 in almost 100% of the simulations, regardless of the true hazard ratio. When upper bound estimates from intent-to-treat were <1.3 and the true hazard ratio = 1, corresponding upper bound estimates from causal analysis were ≥1.3 in up to 66% of the simulations under some settings. LIMITATIONS: Simulations cannot cover all scenarios for noncompliance in real randomized trials. CONCLUSION: Causal survival analysis was superior to intent-to-treat in estimating the true hazard ratio with respect to bias in the presence of noncompliance. However, its large variance should be considered for safety upper bound exclusion especially when the true hazard ratio = 1. Our simulations provided a broad reference for practical considerations of bias-variance trade-off in dealing with noncompliance in cardiovascular safety trials of diabetes drugs. Further research is warranted for the development and application of causal inference methods in the evaluation of safety upper bounds.

SPIRIT 2013 Statement: defining standard protocol items for clinical trials.

The protocol of a clinical trial serves as the foundation for study planning, conduct, reporting, and appraisal. However, trial protocols and existing protocol guidelines vary greatly in content and quality. This article describes the systematic development and scope of SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) 2013, a guideline for the minimum content of a clinical trial protocol. The 33-item SPIRIT checklist applies to protocols for all clinical trials and focuses on content rather than format. The checklist recommends a full description of what is planned; it does not prescribe how to design or conduct a trial. By providing guidance for key content, the SPIRIT recommendations aim to facilitate the drafting of high-quality protocols. Adherence to SPIRIT would also enhance the transparency and completeness of trial protocols for the benefit of investigators, trial participants, patients, sponsors, funders, research ethics committees or institutional review boards, peer reviewers, journals, trial registries, policymakers, regulators, and other key stakeholders.

Bumps and bridges on the road to responsible sharing of clinical trial data.

BACKGROUND: Sharing data from clinical trials could assist with the advancement of science and medicine, potentially providing a better understanding of both the benefits and risks of medicines and other treatments. Sharing data also allows for questions to be addressed at the meta-analysis level that cannot be addressed within individual studies. PURPOSE: In this article, we offer some practical recommendations that will allow researchers to readily combine datasets from different studies and sources, thereby enabling meta-analyses that could have significant impact on advancing medicine. METHODS: The authors relied on their collective experience in the conduct and reporting of clinical trials to define the areas of potential concern related to responsible sharing of clinical trial data. We conducted a review of the literature and engaged in an iterative consensus-building process. RESULTS: To further the goal of responsible sharing of clinical trial data, collaboration on a consistent set of data standards and methods across both industry and academia is sorely needed. Protection of participant privacy is a paramount principle. The additional questions of who maintains, funds, and oversees databases of participant-level data will be important to resolve. Requiring researchers to register their requests for participant-level data and to provide details of their intended research would allow others to evaluate the proposed research plan, consistent with the principles of science and transparency. LIMITATIONS: The recommendations represent the views of the individual authors. We recognize that other approaches to data sharing that have been advocated are also based on sound ethical and scientific principles.