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AbstractWe present a unified three-state model (TSM) framework for evaluating treatment effects in clinical trials in the presence of treatment crossover. Researchers have proposed diverse methodologies to estimate the treatment effect that would have hypothetically been observed if treatment crossover had not occurred. However, there is little work on understanding the connections between these different approaches from a statistical point of view. The proposed TSM framework unifies existing methods, effectively identifying potential biases, model assumptions, and inherent limitations for each method. This can guide researchers in understanding when these methods are appropriate and choosing a suitable approach for their data. The TSM framework also facilitates the creation of new methods to adjust for confounding effects from treatment crossover. To illustrate this capability, we introduce a new imputation method that falls under its scope. Through simulation experiments, we demonstrate the performance of different approaches for estimating the treatment effects. Codes for implementing the methods within the TSM framework are available at https://github.com/JasonZhao111/TSM. [ABSTRACT FROM AUTHOR]

Background Problematic drinking frequently co-occurs with depression among young adults, but often remains unaddressed in depression treatment. Evidence is insufficient on whether digital alcohol interventions can be effective in this young comorbid population. In a randomized controlled trial, we examined the effectiveness of Beating the Booze (BtB), an add-on digital alcohol intervention to complement depression treatment for young adults. Methods Participants were randomized to BtB + depression treatment as usual (BTB + TAU, n = 81) or TAU (n = 82). The primary outcome was treatment response, a combined measure for alcohol and depression after 6-month follow-up. Secondary outcomes were number of weekly drinks (Timeline Follow-back) and depressive symptoms (Center for Epidemiologic Studies Depression scale). Treatment response was analyzed using generalized linear modeling and secondary outcomes using robust linear mixed modeling. Results Low treatment response was found due to lower than expected depression remission rates. No statistically significant between-group effect was found for treatment response after 6-month follow-up (odds ratio 2.86, p = 0.089, 95% confidence interval [CI] 0.85–9.63). For our secondary outcomes, statistically significant larger reductions in weekly drinks were found in the intervention group after 3-month (B = −4.00, p = 0.009, 95% CI −6.97 to −1.02, d = 0.27) and 6-month follow-up (B = −3.20, p = 0.032, 95% CI −6.13 to −0.27, d = 0.23). We found no statistically significant between-group differences on depressive symptoms after 3-month (B = −0.57, p = 0.732, 95% CI −3.83 to 2.69) nor after 6-month follow-up (B = −0.44, p = 0.793, 95% CI −3.69 to 2.82). Conclusions The add-on digital alcohol intervention was effective in reducing alcohol use, but not in reducing depressive symptoms and treatment response among young adults with co-occurring depressive disorders and problematic alcohol use. Trial registration: Pre-registered on October 29, 2019 in the Overview of Medical Research in the Netherlands (OMON), formerly the Dutch Trial Register(https://onderzoekmetmensen.nl/en/trial/49219). [ABSTRACT FROM AUTHOR]

Background: Peripheral artery disease (PAD) is the third most prevalent atherosclerotic cardiovascular disease. In 2016, costs per patient associated with PAD exceeded even the health-economic burden of coronary heart disease. Although affecting over 200 million people worldwide, a clear consensus on the most beneficial components to be included in home-based exercise programs for patients with peripheral artery disease is lacking. The aim of the study was to examine the health care use and costs caused by the 12-month patient-centered 'Telephone Health Coaching and Remote Exercise Monitoring for Peripheral Artery Disease' (TeGeCoach) program in a randomized controlled trial. Methods: This is a two-arm, parallel-group, open-label, pragmatic, randomized, controlled clinical trial (TeGeCoach) at three German statutory health insurance funds with follow-up assessments after 12 and 24-months. Study outcomes were medication use (daily defined doses), days in hospital, sick pay days and health care costs, from the health insurers' perspective. Claims data from the participating health insurers were used for analyses. The main analytic approach was an intention-to-treat (ITT) analysis. Other approaches (modified ITT, per protocol, and as treated) were executed additionally as sensitivity analysis. Random-effects regression models were calculated to determine difference-in-difference (DD) estimators for the first- and the second year of follow-up. Additionally, existing differences at baseline between both groups were treated with entropy balancing to check for the stability of the calculated estimators. Results: One thousand six hundred eighty-five patients (Intervention group (IG) = 806; Control group (CG) = 879) were finally included in ITT analyses. The analyses showed non-significant effects of the intervention on savings (first year: − 352€; second year: − 215€). Sensitivity analyses confirmed primary results and showed even larger savings. Conclusion: Based on health insurance claims data, a significant reduction due to the home-based TeGeCoach program could not be found for health care use and costs in patients with PAD. Nevertheless, in all sensitivity analysis a tendency became apparent for a non-significant cost reducing effect. Trial registration: NCT03496948 (www.clinicaltrials.gov), initial release on 23 March 2018 [ABSTRACT FROM AUTHOR]

Background: Non‐inferiority trials comparing different active drugs are often subject to treatment non‐adherence. Intention‐to‐treat (ITT) and per‐protocol (PP) analyses have been advocated in such studies but are not guaranteed to be unbiased in the presence of differential non‐adherence. Methods: The REMoxTB trial evaluated two 4‐month experimental regimens compared with a 6‐month control regimen for newly diagnosed drug‐susceptible TB. The primary endpoint was a composite unfavorable outcome of treatment failure or recurrence within 18 months post‐randomization. We conducted a simulation study based on REMoxTB to assess the performance of statistical methods for handling non‐adherence in non‐inferiority trials, including: ITT and PP analyses, adjustment for observed adherence, multiple imputation (MI) of outcomes, inverse‐probability‐of‐treatment weighting (IPTW), and a doubly‐robust (DR) estimator. Results: When non‐adherence differed between trial arms, ITT, and PP analyses often resulted in non‐trivial bias in the estimated treatment effect, which consequently under‐ or over‐inflated the type I error rate. Adjustment for observed adherence led to similar issues, whereas the MI, IPTW and DR approaches were able to correct bias under most non‐adherence scenarios; they could not always eliminate bias entirely in the presence of unobserved confounding. The IPTW and DR methods were generally unbiased and maintained desired type I error rates and statistical power. Conclusions: When non‐adherence differs between trial arms, ITT and PP analyses can produce biased estimates of efficacy, potentially leading to the acceptance of inferior treatments or efficacious regimens being missed. IPTW and the DR estimator are relatively straightforward methods to supplement ITT and PP approaches. [ABSTRACT FROM AUTHOR]

In clinical trials that are subject to noncompliance, the commonly used intention-to-treat estimand is valid as a causal effect of treatment assignment but is sensitive to the level of compliance. An alternative estimand, the complier average causal effect (CACE), measures the average effect of treatment received in the latent subset of subjects who would comply with either assigned treatment. Because the principal stratum of compliers can vary with the circumstances of the trial, CACE too depends on the compliance fraction. We propose a model in which an underlying latent proto-compliance interacts with trial characteristics to determine a subject's compliance behavior. When the latent compliance is independent of the individual treatment effect, the average causal effect is constant across compliance classes, and CACE is robust across trials and equal to the population average causal effect. We demonstrate the potential degree of sensitivity of CACE in a simulation study, an analysis of data from a trial of vitamin A supplementation in children, and a meta-analysis of trials of epidural analgesia in labor. [ABSTRACT FROM AUTHOR]

Rationale & Objectives: Hyperglycemia is frequently observed early after transplantation and associated with development of post-transplant diabetes mellitus (PTDM). Here, we assessed continuous subcutaneous insulin infusion (CSII) targeting afternoon hyperglycemia. Study Design: Open-label randomized parallel 3-arm design. Settings & Participants: In total, 85 kidney transplant recipients without previous diabetes diagnosis were randomized to postoperative CSII therapy, basal insulin, or control. Interventions: Insulin was to be initiated at afternoon capillary blood glucose level of ≥140 mg/dL (7.8 mmol/L; CSII and basal insulin) or fasting plasma glucose level of ≥200 mg/dL (11.1 mmol/L; control). Outcomes: Hemoglobin A1c (HbA1c) levels at 3 months post-transplant (primary endpoint). PTDM assessed using oral glucose tolerance test at 12 and 24 months. Results: CSII therapy lasted until median day 18 and maximum day 88. The median HbA1c value at month 3 was 5.6% (38 mmol/mol) in the CSII group versus 5.7% (39 mmol/mol) in the control group (P = 0.70) and 5.4% (36 mmol/mol) in the basal insulin group (P = 0.02). At months 12 and 24, the odds for PTDM were similar compared with the control group (odds ratios [95% confidence intervals], 0.80 [0.18-3.49] and 0.71 [0.15-3.16], respectively) and the basal insulin group (0.96 [0.18-5.68] and 1.51 [0.24-12.84], respectively). Mild hypoglycemia events occurred in the CSII and the basal insulin groups. Limitations: This study is limited by outdated insulin pump technology, frequent discontinuations of CSII, a complex protocol, and concerns regarding reliability of HbA1c measurements. Conclusions: CSII therapy was not superior at reducing HbA1c levels at month 3 or PTDM prevalence at months 12 and 24 compared with the control or basal insulin group.

The paper studies the effects of abolishing fees in the public childcare facilities on the maternal labor supply and provides evidence from a post‐Soviet developing country, Armenia, characterized with low female labor force participation and high unemployment. The reform unexpectedly introduced only in the capital city created a natural experiment which we investigate using difference‐in‐differences methodology. The statistically significant increase of the childcare service utilization is shown to be affecting only marginally the maternal labor supply as measured by intention‐to‐treat effects. The positive results are more robust when only women actually utilizing the services are considered, but all the effects obtained fade out already in the second year after the reform. The robustness of our findings is tested by a series of placebo regressions. [ABSTRACT FROM AUTHOR]

It has recently been suggested that precision oncology studies should be reanalysed using the intention-to-treat (ITT) methodology developed for randomized controlled clinical trials. This reanalysis dramatically decreases response rates in precision medicine studies. We contend that the ITT analysis of precision oncology trials is invalid. The ITT methodology was developed three decades ago to mitigate the problems of randomized trials, which try to ensure that both arms have an unselected patient population free from confounders. In contrast, precision oncology trials specifically select patients for confounders (that is biomarkers) that predict response. To demonstrate the issues inherent in an ITT reanalysis for precision cancer medicine studies, we take as an example the drug larotrectinib (TRK inhibitor) approved because of remarkable responses in malignancies harbouring NTRK fusions. Based on large-scale studies, NTRK fusions are found in ~0.31% of tumours. In a non-randomized pivotal study of larotrectinib, 75% of the 55 treated patients responded. Based upon the prevalence of NTRK fusions, ~18,000 patients would need to be screened to enrol the 55 treated patients. Utilizing the ITT methodology, the revised response rate to larotrectinib would be 0.23%. This is, of course, a dramatic underestimation of the efficacy of this now Food and Drug Administration (FDA)-approved drug. Similar issues can be shown for virtually any biomarker-based precision clinical trial. Therefore, retrofitting the ITT analysis developed for unselected patient populations in randomized trials yields misleading conclusions in precision medicine studies.

Under exceptional circumstances, including high rates of protocol non-compliance, per-protocol (PP) analysis can better indicate the real-world benefits of a medical intervention than intention-to-treat (ITT) analysis. Exemplifying this, the first randomized clinical trial (RCT) considered found that colonoscopy screenings were marginally beneficial, based upon ITT analysis, with only 42% of the intervention group actually undergoing the procedure. However, the study authors themselves concluded that the medical efficacy of that screening was a 50% reduction in colorectal cancer deaths among that 42% PP group. The second RCT found a ten-fold reduction in mortality for a COVID-19 treatment drug vs. placebo by PP analysis, but only a minor benefit by ITT analysis. The third RCT, conducted as an arm of the same platform trial as the second RCT, tested another COVID-19 treatment drug and reported no significant benefit by ITT analysis. Inconsistencies and irregularities in the reporting of protocol compliance for this study required consideration of PP outcomes for deaths and hospitalizations, yet the study coauthors refused to disclose them, instead directing inquiring scientists to a data repository which never held the study's data. These three RCTs illustrate conditions under which PP outcomes may differ significantly from ITT outcomes and the need for data transparency when these reported or indicated discrepancies arise. [ABSTRACT FROM AUTHOR]

The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) E9 (R1) addendum will have an important impact on the design and analysis of randomized controlled clinical trials, which represent crucial sources of evidence in health technology assessments, and on the intention-to-treat (ITT) principle in particular. This article brings together a task force of health economists and statisticians in academic institutes and the pharmaceutical industry, to examine the implications of the addendum from the perspective of the National Institute for Health and Care Excellence (NICE) and the Institut für Qualität und Wirtschaftlichkeit im Gesundheitswesen (IQWiG) and to address the question of whether the ITT principle should be considered the gold standard for estimating treatment effects. We review the ITT principle, as introduced in the ICH E9 guideline. We then present an overview of the ICH E9 (R1) addendum and its estimand framework, highlighting its premise and the proposed strategies for handling intercurrent events, and examine some cases among submissions to IQWiG and NICE. IQWiG and NICE appear to have diverging perspectives around the relevance of the ITT principle and, in particular, the acceptance of hypothetical strategies for estimating treatment effects, as suggested by examples where the sponsor proposed an alternative approach to the ITT principle when accounting for treatment switching for interventional oncology trials. The ICH E9 (R1) addendum supports the use of methods that depart from the ITT principle. The relevance of estimands using these methods depends on the perspectives and objectives of payers. It is challenging to design a study that meets all stakeholders' research questions. Different estimands may serve to answer different relevant questions or decision problems. • The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use E9 (R1) addendum, through the estimand framework, has affirmed the desirability, in certain circumstances, of estimating treatment effects in randomized controlled trials on the basis of strategies that depart from the intention-to-treat principle. • To the best of our knowledge, there have been limited attempts to date to assess the implications of the addendum for health technology assessment decision making. • To help with this shortfall, we discuss the perspectives of 2 agencies, the Institut für Qualität und Wirtschaftlichkeit im Gesundheitswesen and the National Institute for Health and Care Excellence, on the intention-to-treat principle, building on our understanding of published methods guidance, publicly available agency documents, and our experience of working with these agencies. [ABSTRACT FROM AUTHOR]

Introduction: Randomized controlled trials are used to estimate the causal effect of a treatment on a health outcome of interest in a patient population. Often the specified treatment in a randomized controlled trial is a medical intervention—such as a drug or procedure—experienced directly by the patient. Sometimes the "treatment" in a randomized controlled trial is a target—such as a goal biomarker measurement—that the patient's physician attempts to reach using available medications or procedures. Large randomized controlled trials of biomarker targets are common in clinical research, and trials have been conducted to compare targets in the management of hypertension, diabetes, anemia, and acute respiratory distress syndrome. However, different randomized controlled trials intended to evaluate the same biomarker targets have produced conflicting recommendations, and meta-analyses that aggregate results of trials of biomarker targets have been inconclusive. Methods: We use causal reasoning to explain why randomized controlled trials of biomarker targets can arrive at conflicting or misleading conclusions. We describe four key threats to the validity of trials of targets: (1) intention-to-treat analysis can be misleading when a direct effect of target assignment on the outcome exists due to lack of blinding; (2) incomparability in results across trials of targets; (3) time-varying adaptive treatment strategies; and (4) Goodhart's law, "when a measure becomes a target, it ceases to be a good measure." Results: We illustrate these findings using evidence from 15 randomized controlled trials of blood pressure targets for management of hypertension. Randomized trials of blood pressure targets exhibit substantial variation in the trial patient populations and antihypertensives used to achieve the blood pressure targets assigned in the trials. The trials did not compare or account for time-varying treatment strategies used to reach the randomized targets. Possible "off-target" effects of antihypertensive medications needed to reach lower blood pressure targets may explain the absence of a clear benefit from intensive blood pressure control. Discussion: Researchers should critically assess meta-analyses of trials of targets for variation in the types, distributions, and off-target effects of therapies studied. Trial investigators should release detailed information about the biomarker targets compared in new randomized trials, as well as confounders, treatments delivered, and outcomes. New randomized controlled trials should experimentally compare treatment algorithms incorporating biomarkers, rather than targets alone. Causal inference methodology that adjusts for time-varying confounding should be used to compare time-varying treatment strategies in observational settings. [ABSTRACT FROM AUTHOR]

It is healthy to periodically question things that we have long taken for granted. Randomized clinical trials are the gold standard for evaluating the benefits and harms of interventions, though often fails to provide the practical evidence to inform medical decision-making. A primary reason is failure to recognize the most important questions for treating patients in clinical practice, and using this as the motivation for the design, monitoring, analysis, and reporting of clinical trials. Our most promising opportunity is placing increased interest on questions of a pragmatic origin to match their clinical importance. Improvements to traditional approaches are needed. Standard approaches synthesizing information obtained from separate marginal analysis of each outcome, fail to incorporate associations between outcomes and recognize the cumulative nature of outcomes in individual patients, suffer from competing risk complexities during interpretation of individual outcomes, and since efficacy and safety analyses are often conducted on different populations, generalizability is unclear. The utility of clinical trials can be enhanced by: (i) using outcomes to analyze patients rather than patients to analyze the outcomes, and (ii) incorporating benefit:risk evaluation into standard trial design and conduct, rather than conducted as a post-hoc exercise. Benefit: risk outcomes such as the desirability of outcome ranking (DOOR), can become a standard, prespecified along with efficacy and safety outcomes. Inclusion and analyses of such endpoints provide important information regarding the effects on patients, unable to be obtained by marginal analyses of efficacy and safety. Prespecified procedures to identify subgroups of patients with a positive benefit:risk profile will further advance clinical trial science. [ABSTRACT FROM AUTHOR]

Donnie Funch,1 Kathleen Mortimer,1 Najat J Ziyadeh,1 John D Seeger,1 Li Zhou,1 Eva Ng,1 Douglas Ross,2,3 Atheline Major-Pedersen,4 Heidrun Bosch-Traberg,5 Helge Gydesen,6 David D Dore1,7 1Optum Epidemiology, Boston, MA, USA; 2Massachusetts General Hospital, Thyroid Associates, Boston, MA, USA; 3Harvard Medical School, Department of Medicine, Boston, MA, USA; 4Global Safety, Novo Nordisk A/S, Copenhagen, Denmark; 5Global Development, Novo Nordisk A/S, Copenhagen, Denmark; 6Epidemiology, Novo Nordisk A/S, Copenhagen, Denmark; 7Department of Health Services, Policy & Practice, Brown University School of Public Health, Providence, RI, USACorrespondence: Najat J ZiyadehOptum Epidemiology, 1325 Boylston Street, 11th Floor, Boston, MA, 02215, USAEmail najat.ziyadeh@optum.comBackground: Quantify association between the glucagon-like peptide-1 receptor agonist liraglutide and risk of thyroid cancer (TC) compared to other antidiabetics.Patients and Methods: Initiators of liraglutide, exenatide, metformin, pioglitazone or groups of dipeptidyl peptidase-4 inhibitors or sulfonylureas were identified in a US health plan (2010– 2014) and followed for a median of 17 months. Thyroid cancer cases during follow-up were identified via a validated algorithm. Incidence rates of TC among liraglutide and comparators were assessed using relative risks estimated within propensity score-matched cohorts using intention to treat (ITT) and time on drug analyses. Latency effects and potential surveillance bias were evaluated.Results: Relative risks from ITT analyses ranged from 1.00 (95% confidence interval (CI) 0.56– 1.79) versus metformin to 1.70 (95% CI 1.03– 2.81) versus all comparators excluding exenatide. Effect estimates from latency analyses were slightly attenuated. Time on drug analyses suggested no increased risk for either longer duration or higher cumulative dose of liraglutide. Medical record review found 85% were papillary or a follicular variant of papillary or both; 46% were microcarcinomas (≤ 10 millimeters), which were more prevalent in the liraglutide cohort (67% versus 43% in all comparators).Conclusion: Relative risks were elevated for several comparisons, which should be interpreted cautiously because of potential residual confounding and surveillance bias. Liraglutide cases had smaller thyroid nodules and shorter time-to-diagnosis, suggesting increased surveillance for TC among liraglutide initiators, especially shortly after the drug´s approval. After adjusting the primary analyses (ITT) for latency, no significant elevated risk of TC was observed among liraglutide initiators.Keywords: glucagon-like peptide-1 receptor agonist, type 2 diabetes, administrative claims, intention-to-treat, time-on-drug

Objectives: This paper illustrates survival models for analysis of trials of substance use treatment programs. It uses public release data from a study of extended-release naltrexone (XR-NTX), relative to buprenorphine-naloxone (BUP-NX). Methods: We used publicly available data from the X:BOT trial (n = 570), which compared XR-NTX to BUP-NX on 2 efficacy outcomes (opioid relapse, use of nonprescribed opioids; positive opioid urine test) and 1 safety outcome (overdose). Intention-to-treat (ITT) and per-protocol approaches were implemented using survival models that included treatment-by-time interactions. Results: Consistent with the original trial findings, 72% of XR-NTX and 94% of BUP-NX subjects initiated treatment; the ITT hazard ratio for XR-NTX relative to BUP-NX was 1.40 (95% confidence interval: 1.13, 1.73; P < 0.01) for opioid relapse and 1.31 (1.07, 1.60; P = 0.01) for positive urine test. Using treatment-by-time interactions, we examined the time-dependent effect of XR-NTX and found an elevated ITT overdose hazard ratio of 2.4 (1.1, 5.3; P = 0.03) overall and 3.8 (1.2, 11.6; P = 0.02) during the study treatment phase. This result (28 overdoses overall; 17 overdoses during the study treatment phase) contrasts with the previous analysis, which reported minimal differences in overdose between XR-NTX and BUP-NX. Conclusions: An advantage of using time-dependent Cox models is its ability to isolate effects during specific periods. In general, our survival analyses concur with the conclusions of Lee et al (2018) for the efficacy outcomes, which demonstrated superiority of BUP-NX. In contrast to the original report, our analysis indicates a greater risk of overdose for XR-NTX, predominantly during the study treatment phase. Further investigation of this finding is a pressing research priority. [ABSTRACT FROM AUTHOR]

Abstract Background In non-inferiority trials, there is a concern that intention-to-treat (ITT) analysis, by including participants who did not receive the planned interventions, may bias towards making the treatment and control arms look similar and lead to mistaken claims of non-inferiority. In contrast, per protocol (PP) analysis is viewed as less likely to make this mistake and therefore preferable in non-inferiority trials. In a systematic review of antibiotic non-inferiority trials, we compared ITT and PP analyses to determine which analysis was more conservative. Methods In a secondary analysis of a systematic review, we included non-inferiority trials that compared different antibiotic regimens, used absolute risk reduction (ARR) as the main outcome and reported both ITT and PP analyses. All estimates and confidence intervals (CIs) were oriented so that a negative ARR favored the control arm, and a positive ARR favored the treatment arm. We compared ITT to PP analyses results. The more conservative analysis between ITT and PP analyses was defined as the one having a more negative lower CI limit. Results The analysis included 164 comparisons from 154 studies. In terms of the ARR, ITT analysis yielded the more conservative point estimate and lower CI limit in 83 (50.6%) and 92 (56.1%) comparisons respectively. The lower CI limits in ITT analysis favored the control arm more than in PP analysis (median of − 7.5% vs. -6.9%, p = 0.0402). CIs were slightly wider in ITT analyses than in PP analyses (median of 13.3% vs. 12.4%, p

Abstract Background Neoadjuvant therapy has several potential advantages over upfront surgery in patients with localized pancreatic cancer; more patients receive systemic treatment, fewer patients undergo futile surgery, and R0 resection rates are higher, thereby possibly improving overall survival (OS). Two recent randomized trials have suggested benefit of neoadjuvant chemoradiotherapy over upfront surgery, both including single-agent chemotherapy regimens. Potentially, the multi-agent FOLFIRINOX regimen (5-fluorouracil with leucovorin, irinotecan, and oxaliplatin) may further improve outcomes in the neoadjuvant setting for localized pancreatic cancer, but randomized studies are needed. The PREOPANC-2 trial investigates whether neoadjuvant FOLFIRINOX improves OS compared with neoadjuvant gemcitabine-based chemoradiotherapy and adjuvant gemcitabine in resectable and borderline resectable pancreatic cancer patients. Methods This nationwide multicenter phase III randomized controlled trial includes patients with pathologically confirmed resectable and borderline resectable pancreatic cancer with a WHO performance score of 0 or 1. Resectable pancreatic cancer is defined as no arterial and ≤ 90 degrees venous involvement; borderline resectable pancreatic cancer is defined as ≤90 degrees arterial and ≤ 270 degrees venous involvement without occlusion. Patients receive 8 cycles of neoadjuvant FOLFIRINOX chemotherapy followed by surgery without adjuvant treatment (arm A), or 3 cycles of neoadjuvant gemcitabine with hypofractionated radiotherapy (36 Gy in 15 fractions) during the second cycle, followed by surgery and 4 cycles of adjuvant gemcitabine (arm B). The primary endpoint is OS by intention-to-treat. Secondary endpoints include progression-free survival, quality of life, resection rate, and R0 resection rate. To detect a hazard ratio of 0.70 with 80% power, 252 events are needed. The number of events is expected to be reached after inclusion of 368 eligible patients assuming an accrual period of 3 years and 1.5 years follow-up. Discussion The PREOPANC-2 trial directly compares two neoadjuvant regimens for patients with resectable and borderline resectable pancreatic cancer. Our study will provide evidence on the neoadjuvant treatment of choice for patients with resectable and borderline resectable pancreatic cancer. Trial registration Primary registry and trial identifying number: EudraCT: 2017–002036-17 . Date of registration: March 6, 2018. Secondary identifying numbers: The Netherlands National Trial Register – NL7094 , NL61961.078.17, MEC-2018-004.

There is an innate desire to conduct research faster and cheaper. The desire is magnified by todays' business and political pressures. Though understandable, such desires can be dangerous threatening our objectivity and ability to reason, resulting in studies with lower integrity, replicability, and applicability. Modern ideas include: conducting observational rather than randomized studies rationalized by the increasing access to real world data and the belief that modeling can replace randomization, using surrogate rather than clinical outcomes, using surrogate rather than clinical diseases, using PP (Per Protocol) analyses instead of ITT (Intention-to-Treat), using assumptions regarding treatment effects in place of data to estimate those effects, and using adaptive designs that promise efficiencies. These trends are often labeled as "innovation." But is this progress...or regress...a fancy way of lowering the usual evidentiary standard and introducing greater uncertainty? Is it time for a market correction for these "products" that are often presented with a degree of commercialism rather than scientific objectivity? Indeed, our traditional approaches are in need in improvements. Rather than compromising on scientific rigor, can we redirect our motivation to find BETTER answers to the most important questions for patients and clinicians? Though often misunderstood, one such movement is pragmatism, the concept of truly getting closer to understanding the effects of interventions as they are experienced by patients and the value of diagnostics in real world practice. I propose that we place increased interest on questions of a pragmatic origin to match their clinical importance and utility. I present ideas for more pragmatic assessments of the effects of interventions and the yield of diagnostics. [ABSTRACT FROM AUTHOR]

Background and Aims: Morphometric features such as the Milan criteria serve as standard criteria for liver transplantation (LT) in patients with hepatocellular carcinoma (HCC). Since it has been recognized that these criteria are too restrictive and do not adequately display the tumor biology, additional selection parameters are emerging. Methods: Concise review of the current literature on patient selection for downstaging and LT for HCC outside the Milan criteria. Results: The major task in patients outside the Milan criteria is the need for higher granularity with patient selection, since the benefit through LT is not uniform. The recent literature clearly shows that beneath tumor size and number, additional selection parameters are useful in the process of patient selection for and during downstaging. For initial patient selection, the alpha fetoprotein (AFP) level adds additional information to the size and number of HCC nodules concerning the chance of successful downstaging and LT. This effect is quantifiable using newer selection tools like the WE (West-Eastern) downstaging criteria or the Metroticket 2.0 criteria. Also an initial PET-scan and/or tumor biopsy can be helpful, especially in the high risk group of patients outside the University of California San Francisco (UCSF) criteria. After this entry selection, the clinical course during downstaging procedures concerning the tumor and the AFP response is of paramount importance and serves as an additional final selection tool. Conclusion: Selection criteria for liver transplantation in HCC patients are becoming more and more sophisticated, but are still imperfect. The implementation of molecular knowledge will hopefully support a more specific risk prediction for HCC patients in the future, but do not provide a profound basis for clinical decision-making at present. [ABSTRACT FROM AUTHOR]

Abstract Background An estimand defines the target of estimation for a clinical trial through specification of the treatment, target population, variable, population-level summary and of the strategies for intercurrent events. A carefully defined estimand aligns the clinical trial design and analysis with the scientific question of interest and adequately accounts for so-called intercurrent events. The ICH E9(R1) addendum suggests five estimand strategies. We evaluated to what extent current practice in drug development and regulatory assessment fits in the estimand framework. Methods We systematically evaluated what estimands, especially what strategies for intercurrent events are advised in European Medicines Agency disease guidelines, used in sponsors’ trials and additionally requested by the European Medicines Agency in assessment dossiers. We selected four therapeutic areas: nervous system, oncology, cardiovascular diseases and respiratory diseases. For each, we evaluated all disease guidelines with approved drugs, the dossiers of the most recently approved drugs matching the guidelines and corresponding regulatory questions. Results Strategies for intercurrent events were present in 18 (53%) of 34 guidelines, in all 34 sponsor documentations and in 15 (44%) of 34 sets of regulatory questions. Treatment policy was advised in 13 (38%) guidelines and was applied in 9 corresponding sponsor documentations. Of these 9, it was the sole strategy in 4 cases and accompanied by another strategy in 5 cases. Hypothetical strategy was not advised in guidelines. However, it was the leading strategy applied in 25 (74%) sponsor documentations. Composite strategy was advised in 3 (9%) guidelines and applied accompanied by another strategy in 2 corresponding sponsor documentations. While on treatment strategy was not advised in guidelines, but was applied in 2 sponsor documentations. Principal stratum strategy was advised in 2 guidelines but not applied in corresponding sponsor documentations. Of the regulatory questions, treatment policy was present in 2 cases (6%), hypothetical in 6 cases (18%), composite in 6 cases (18%) and while on treatment in 1 case (3%). Conclusions Estimand attributes are present in guidelines, sponsor documentations and regulatory questions, but not described as estimands. Treatment policy was most often advised in guidelines, but hypothetical was the leading strategy applied in sponsor documentations. Thus, results indicate not a full concordance between the regulatory target of estimation and what is actually estimated. The lack of concordance was mostly due to limitations in collection of intercurrent events data to enable a treatment policy strategy. There is, therefore, a need to better define estimands at the design stage and throughout the applications dossiers and assessment reports.

Background In the GLOBAL LEADERS trial, ticagrelor monotherapy beyond 1 month compared with standard antiplatelet regimens after coronary stent implantation did not improve outcomes at intention‐to‐treat analysis. Considerable differences in treatment adherence between the experimental and control groups may have affected the intention‐to‐treat results. In this reanalysis of the GLOBAL LEADERS trial, we compared the experimental and control treatment strategies in a per‐protocol analysis of patients who did not deviate from the study protocol. Methods and Results Baseline and postrandomization information were used to classify whether and when patients were deviating from the study protocol. With logistic regressions, we derived time‐varying inverse probabilities of nondeviation from protocol to reconstruct the trial population without protocol deviation. The primary end point was a composite of all‐cause mortality or nonfatal Q‐wave myocardial infarction at 2 years. At 2‐year follow‐up, 1103 (13.8%) of 7980 patients in the experimental group and 785 (9.8%) of 7988 patients in the control group qualified as protocol deviators. At per‐protocol analysis, the rate ratio for the primary end point was 0.88 (95% CI, 0.75–1.03; P=0.10) on the basis of 274 versus 325 events in the experimental versus control group. The rate ratio for the key safety end point of major bleeding was 1.00 (95% CI, 0.79–1.26; P=0.99). The per‐protocol and intention‐to‐treat effect estimates were overall consistent. Conclusions Among patients who complied with the study protocol in the GLOBAL LEADERS trial, ticagrelor plus aspirin for 1 month followed by ticagrelor monotherapy was not superior to 1‐year standard dual antiplatelet therapy followed by aspirin alone at 2 years after coronary stenting. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT01813435.

Purpose of reviewWe discuss selected statistical issues in the design and analysis of preexposure prophylaxis (PrEP) trials. The general principles may inform thinking for other interventions in HIV prevention.Recent findingsTo date, four different designs have been used to determine the effectiveness of PrEP: randomized, double-blind, placebo-controlled; randomized, open-label, immediate or delayed access; nonrandomized comparison of HIV incidence according to the level of drug detected; comparison of the observed HIV incidence to the expected rate using historical control data. Open-label trials of PrEP, which assess public health effectiveness, complement the placebo-controlled trials which established the biological efficacy of TDF/FTC. Future trials of PrEP will be highly challenging to design since a no PrEP group is difficult to justify and the natural control regimen, TDF/FTC, is highly efficacious.SummaryStandard statistical paradigms for noninferiority trials should be reconsidered for evaluating alternative PrEP regimens.

Background: In cluster randomized trials, patients are typically recruited after clusters are randomized, and the recruiters and patients may not be blinded to the assignment. This often leads to differential recruitment and consequently systematic differences in baseline characteristics of the recruited patients between intervention and control arms, inducing post-randomization selection bias. We aim to rigorously define causal estimands in the presence of selection bias. We elucidate the conditions under which standard covariate adjustment methods can validly estimate these estimands. We further discuss the additional data and assumptions necessary for estimating causal effects when such conditions are not met. Methods: Adopting the principal stratification framework in causal inference, we clarify there are two average treatment effect (ATE) estimands in cluster randomized trials: one for the overall population and one for the recruited population. We derive analytical formula of the two estimands in terms of principal-stratum-specific causal effects. Furthermore, using simulation studies, we assess the empirical performance of the multivariable regression adjustment method under different data generating processes leading to selection bias. Results: When treatment effects are heterogeneous across principal strata, the average treatment effect on the overall population generally differs from the average treatment effect on the recruited population. A naïve intention-to-treat analysis of the recruited sample leads to biased estimates of both average treatment effects. In the presence of post-randomization selection and without additional data on the non-recruited subjects, the average treatment effect on the recruited population is estimable only when the treatment effects are homogeneous between principal strata, and the average treatment effect on the overall population is generally not estimable. The extent to which covariate adjustment can remove selection bias depends on the degree of effect heterogeneity across principal strata. Conclusion: There is a need and opportunity to improve the analysis of cluster randomized trials that are subject to post-randomization selection bias. For studies prone to selection bias, it is important to explicitly specify the target population that the causal estimands are defined on and adopt design and estimation strategies accordingly. To draw valid inferences about treatment effects, investigators should (1) assess the possibility of heterogeneous treatment effects, and (2) consider collecting data on covariates that are predictive of the recruitment process, and on the non-recruited population from external sources such as electronic health records. [ABSTRACT FROM AUTHOR]

Abstract Background Cluster randomized trials (CRTs) are a design used to test interventions where individual randomization is not appropriate. The mixed model for repeated measures (MMRM) is a popular choice for individually randomized trials with longitudinal continuous outcomes. This model’s appeal is due to avoidance of model misspecification and its unbiasedness for data missing completely at random or at random. Methods We extended the MMRM to cluster randomized trials by adding a random intercept for the cluster and undertook a simulation experiment to investigate statistical properties when data are missing at random. We simulated cluster randomized trial data where the outcome was continuous and measured at baseline and three post-intervention time points. We varied the number of clusters, the cluster size, the intra-cluster correlation, missingness and the data-generation models. We demonstrate the MMRM-CRT with an example of a cluster randomized trial on cardiovascular disease prevention among diabetics. Results When simulating a treatment effect at the final time point we found that estimates were unbiased when data were complete and when data were missing at random. Variance components were also largely unbiased. When simulating under the null, we found that type I error was largely nominal, although for a few specific cases it was as high as 0.081. Conclusions Although there have been assertions that this model is inappropriate when there are more than two repeated measures on subjects, we found evidence to the contrary. We conclude that the MMRM for CRTs is a good analytic choice for cluster randomized trials with a continuous outcome measured longitudinally. Trial registration ClinicalTrials.gov, ID: NCT02804698.

Background: Stress fractures are a common and potentially debilitating overuse injury to bone and occur frequently among military recruits and athletes. Recovery from a lower body stress fracture typically requires several weeks of physical rehabilitation. Teriparatide, a recombinant form of the bioactive portion of parathyroid hormone (1-34 amino acids), is used to treat osteoporosis, prevent osteoporotic fractures, and enhance fracture healing due to its net anabolic effect on bone. The study aim is to investigate the effect of teriparatide on stress fracture healing in young, otherwise healthy adults undergoing military training.Methods: In a two-arm, parallel, prospective, randomised controlled, intention-to-treat trial, Army recruits (n = 136 men and women, 18-40 years) with a magnetic resonance imaging (MRI) diagnosed lower body stress fracture (pelvic girdle, sacrum, coccyx, or lower limb) will be randomised to receive either usual Army standard care, or teriparatide and usual Army standard care. Teriparatide will be self-administered by subcutaneous injections (20 μg/day) for 16 weeks, continuing to 24 weeks where a fracture remains unhealed at week 16. The primary outcome will be the improvement in radiological healing by two grades or more, or reduction to grade zero, 8 weeks after randomisation, assessed using Fredericson grading of MRI by radiologists blind to the randomisation. Secondary outcomes will be time to radiological healing, assessed by MRI at 8, 10, 12, 14, 16, 20 and 24 weeks, until healed; time to clinical healing, assessed using a clinical severity score of injury signs and symptoms; time to discharge from Army physical rehabilitation; pain, assessed by visual analogue scale; health-related quality of life, using the Short Form (36) Health Survey; and adverse events. Exploratory outcomes will include blood and urine biochemistry; bone density and morphology assessed using dual-energy X-ray absorptiometry, peripheral quantitative computed tomography (pQCT), and high-resolution pQCT; physical activity measured using accelerometers; and long-term future fracture rate.Discussion: This study will evaluate whether teriparatide, in addition to standard care, is more effective for stress fracture healing than standard care alone in Army recruits who have sustained a lower body stress fracture.Trial Registration: ClinicalTrials.gov NCT04196855 . Registered on 12 December 2019. [ABSTRACT FROM AUTHOR]

Objectives: This paper examines whether the posting of sticker decals indicating the use of forensic property marking deters burglary. Methods: The study is a randomized controlled trial (RCT). The sampling frame includes all (N = 6603) single-family houses in the municipality of Aarhus, Denmark, that were burgled once or more during the 4 years prior to the experiment. Houses were randomly assigned to treatment (n = 3378) and control (n = 3225). Treatment houses were offered a free forensic property marking kit and asked to post sticker decals around their front doors indicting their use of the product. Control households were not contacted. Results: A process evaluation determined that only one-third (n = 1080) of the houses assigned to treatment requested property marking kits and posted stickers as instructed. An intention-to-treat (ITT) effect analysis was based on the full treatment group despite a low (32%) compliance rate. At the end of a 15½-month observation period, the full treatment group had experienced 21% fewer burglaries than the control group – a difference that is both substantively and statistically significant (χ2 = 5.305, p = 0.021 n = 6608). Analysis revealed that the preventive effect was limited to the beginning of the observation period and declined thereafter. It is therefore possible that some of the overall result may have been due to an "availability effect," i.e., a heightened vigilance induced by the initial contact letter. Conclusions: The preventive effect of treatment seems incontestable. This said, the full pattern of results suggests that the reduction in burglary was likely due to a combination of treatment and availability effects. [ABSTRACT FROM AUTHOR]

Background: In non-inferiority trials, there is a concern that intention-to-treat (ITT) analysis, by including participants who did not receive the planned interventions, may bias towards making the treatment and control arms look similar and lead to mistaken claims of non-inferiority. In contrast, per protocol (PP) analysis is viewed as less likely to make this mistake and therefore preferable in non-inferiority trials. In a systematic review of antibiotic non-inferiority trials, we compared ITT and PP analyses to determine which analysis was more conservative.Methods: In a secondary analysis of a systematic review, we included non-inferiority trials that compared different antibiotic regimens, used absolute risk reduction (ARR) as the main outcome and reported both ITT and PP analyses. All estimates and confidence intervals (CIs) were oriented so that a negative ARR favored the control arm, and a positive ARR favored the treatment arm. We compared ITT to PP analyses results. The more conservative analysis between ITT and PP analyses was defined as the one having a more negative lower CI limit.Results: The analysis included 164 comparisons from 154 studies. In terms of the ARR, ITT analysis yielded the more conservative point estimate and lower CI limit in 83 (50.6%) and 92 (56.1%) comparisons respectively. The lower CI limits in ITT analysis favored the control arm more than in PP analysis (median of - 7.5% vs. -6.9%, p = 0.0402). CIs were slightly wider in ITT analyses than in PP analyses (median of 13.3% vs. 12.4%, p < 0.0001). The median success rate was 89% (interquartile range IQR 82 to 93%) in the PP population and 44% (IQR 23 to 60%) in the patients who were included in the ITT population but excluded from the PP population (p < 0.0001).Conclusions: Contrary to common belief, ITT analysis was more conservative than PP analysis in the majority of antibiotic non-inferiority trials. The lower treatment success rate in the ITT analysis led to a larger variance and wider CI, resulting in a more conservative lower CI limit. ITT analysis should be mandatory and considered as either the primary or co-primary analysis for non-inferiority trials.Trial Registration: PROSPERO registration number CRD42020165040 . [ABSTRACT FROM AUTHOR]

Background: Neoadjuvant therapy has several potential advantages over upfront surgery in patients with localized pancreatic cancer; more patients receive systemic treatment, fewer patients undergo futile surgery, and R0 resection rates are higher, thereby possibly improving overall survival (OS). Two recent randomized trials have suggested benefit of neoadjuvant chemoradiotherapy over upfront surgery, both including single-agent chemotherapy regimens. Potentially, the multi-agent FOLFIRINOX regimen (5-fluorouracil with leucovorin, irinotecan, and oxaliplatin) may further improve outcomes in the neoadjuvant setting for localized pancreatic cancer, but randomized studies are needed. The PREOPANC-2 trial investigates whether neoadjuvant FOLFIRINOX improves OS compared with neoadjuvant gemcitabine-based chemoradiotherapy and adjuvant gemcitabine in resectable and borderline resectable pancreatic cancer patients.Methods: This nationwide multicenter phase III randomized controlled trial includes patients with pathologically confirmed resectable and borderline resectable pancreatic cancer with a WHO performance score of 0 or 1. Resectable pancreatic cancer is defined as no arterial and ≤ 90 degrees venous involvement; borderline resectable pancreatic cancer is defined as ≤90 degrees arterial and ≤ 270 degrees venous involvement without occlusion. Patients receive 8 cycles of neoadjuvant FOLFIRINOX chemotherapy followed by surgery without adjuvant treatment (arm A), or 3 cycles of neoadjuvant gemcitabine with hypofractionated radiotherapy (36 Gy in 15 fractions) during the second cycle, followed by surgery and 4 cycles of adjuvant gemcitabine (arm B). The primary endpoint is OS by intention-to-treat. Secondary endpoints include progression-free survival, quality of life, resection rate, and R0 resection rate. To detect a hazard ratio of 0.70 with 80% power, 252 events are needed. The number of events is expected to be reached after inclusion of 368 eligible patients assuming an accrual period of 3 years and 1.5 years follow-up.Discussion: The PREOPANC-2 trial directly compares two neoadjuvant regimens for patients with resectable and borderline resectable pancreatic cancer. Our study will provide evidence on the neoadjuvant treatment of choice for patients with resectable and borderline resectable pancreatic cancer.Trial Registration: Primary registry and trial identifying number: EudraCT: 2017-002036-17 . Date of registration: March 6, 2018. Secondary identifying numbers: The Netherlands National Trial Register - NL7094 , NL61961.078.17, MEC-2018-004. [ABSTRACT FROM AUTHOR]

Donnie Funch,1 Kathleen Mortimer,1 Ling Li,1 Heather Norman,1 Atheline Major-Pedersen,2 Anne Helene Olsen,3 Margit S Kaltoft,4 David D Dore1,5 1Optum Epidemiology, Boston, MA, USA; 2Global Safety, Novo Nordisk A/S, Copenhagen, Denmark; 3Epidemiology, Novo Nordisk A/S, Copenhagen, Denmark; 4Global Development, Novo Nordisk A/S, Copenhagen, Denmark; 5Department of Health Services, Policy & Practice, Brown University School of Public Health, Providence, RI, USA Background: Liraglutide is a human glucagon-like peptide-1 receptor agonist approved for treatment of adults with type 2 diabetes mellitus at a maximum dose of 1.8 mg/day (Victoza®) and more recently at 3.0 mg/day for weight management (Saxenda®). During the evaluation of liraglutide for approval in weight management, a minor imbalance in the numbers of reported breast neoplasms was observed, motivating the present study. Our objective was to quantify the association between liraglutide and incidence of breast cancer (BC) among women in a real-world setting. Patients and methods: Women initiating liraglutide or other antidiabetic therapies and who were enrolled in a large US health plan (2010–2014) were included. Comparisons of BC incidence rates were made between matched cohorts of initiators of liraglutide and cohorts of initiators of exenatide, metformin, pioglitazone, sulfonylureas, and dipeptidyl peptidase-4 inhibitors separately and as two “all comparators” groupings: with or without exenatide. Women with two or more claims with BC diagnosis codes within 61days of each other were identified as possible cases, with additional confirmation by clinician review of comprehensive claims listings. Propensity score matched intention-to-treat (ITT) and time-on-drug (TOD) analyses were completed via Poisson regression. A latency analysis was performed. Results: Relative risks for BC for liraglutide vs comparators from the ITT analyses ranged from 0.90 (95% CI: 0.67–1.22) for both the “all comparator” and “all comparator except exenatide” cohorts to 1.46 (95% CI: 0.96–2.22) relative to exenatide. Latency analyses excluding the first year of follow-up yielded slightly attenuated point estimates. The TOD analyses of cumulative use of liraglutide suggested no increased risk of BC. Conclusion: Neither the ITT (overall or latency analysis) nor cumulative TOD analyses suggested an elevated risk of BC among liraglutide initiators. Short length of follow-up and the potential for confounding by unmeasured factors limit the full assessment of long-term risk. Keywords: glucagon-like peptide-1 receptor agonist, type 2 diabetes, administrative claims, intention-to-treat, time-on-drug

Background/aims: Noninferiority clinical trials are susceptible to false confirmation of noninferiority when the intention-to-treat principle is applied in the setting of incomplete trial protocol adherence. The risk increases as protocol adherence rates decrease. The objective of this study was to compare protocol adherence and hypothesis confirmation between superiority and noninferiority randomized clinical trials published in three high impact medical journals. We hypothesized that noninferiority trials have lower protocol adherence and greater hypothesis confirmation. Methods: We conducted an observational study using published clinical trial data. We searched PubMed for active control, two-arm parallel group randomized clinical trials published in JAMA: The Journal of the American Medical Association, The New England Journal of Medicine, and The Lancet between 2007 and 2017. The primary exposure was trial type, superiority versus noninferiority, as determined by the hypothesis testing framework of the primary trial outcome. The primary outcome was trial protocol adherence rate, defined as the number of randomized subjects receiving the allocated intervention as described by the trial protocol and followed to primary outcome ascertainment (numerator), over the total number of subjects randomized (denominator). Hypothesis confirmation was defined as affirmation of noninferiority or the alternative hypothesis for noninferiority and superiority trials, respectively. Results: Among 120 superiority and 120 noninferiority trials, median and interquartile protocol adherence rates were 91.5 [81.4–96.7] and 89.8 [83.6–95.2], respectively; P = 0.47. Hypothesis confirmation was observed in 107/120 (89.2%) of noninferiority and 64/120 (53.3%) of superiority trials, risk difference (95% confidence interval): 35.8 (25.3–46.3), P < 0.001. Conclusion: Protocol adherence rates are similar between superiority and noninferiority trials published in three high impact medical journals. Despite this, we observed greater hypothesis confirmation among noninferiority trials. We speculate that publication bias, lenient noninferiority margins and other sources of bias may contribute to this finding. Further study is needed to identify the reasons for this observed difference. [ABSTRACT FROM AUTHOR]

Background: An estimand defines the target of estimation for a clinical trial through specification of the treatment, target population, variable, population-level summary and of the strategies for intercurrent events. A carefully defined estimand aligns the clinical trial design and analysis with the scientific question of interest and adequately accounts for so-called intercurrent events. The ICH E9(R1) addendum suggests five estimand strategies. We evaluated to what extent current practice in drug development and regulatory assessment fits in the estimand framework.Methods: We systematically evaluated what estimands, especially what strategies for intercurrent events are advised in European Medicines Agency disease guidelines, used in sponsors' trials and additionally requested by the European Medicines Agency in assessment dossiers. We selected four therapeutic areas: nervous system, oncology, cardiovascular diseases and respiratory diseases. For each, we evaluated all disease guidelines with approved drugs, the dossiers of the most recently approved drugs matching the guidelines and corresponding regulatory questions.Results: Strategies for intercurrent events were present in 18 (53%) of 34 guidelines, in all 34 sponsor documentations and in 15 (44%) of 34 sets of regulatory questions. Treatment policy was advised in 13 (38%) guidelines and was applied in 9 corresponding sponsor documentations. Of these 9, it was the sole strategy in 4 cases and accompanied by another strategy in 5 cases. Hypothetical strategy was not advised in guidelines. However, it was the leading strategy applied in 25 (74%) sponsor documentations. Composite strategy was advised in 3 (9%) guidelines and applied accompanied by another strategy in 2 corresponding sponsor documentations. While on treatment strategy was not advised in guidelines, but was applied in 2 sponsor documentations. Principal stratum strategy was advised in 2 guidelines but not applied in corresponding sponsor documentations. Of the regulatory questions, treatment policy was present in 2 cases (6%), hypothetical in 6 cases (18%), composite in 6 cases (18%) and while on treatment in 1 case (3%).Conclusions: Estimand attributes are present in guidelines, sponsor documentations and regulatory questions, but not described as estimands. Treatment policy was most often advised in guidelines, but hypothetical was the leading strategy applied in sponsor documentations. Thus, results indicate not a full concordance between the regulatory target of estimation and what is actually estimated. The lack of concordance was mostly due to limitations in collection of intercurrent events data to enable a treatment policy strategy. There is, therefore, a need to better define estimands at the design stage and throughout the applications dossiers and assessment reports. [ABSTRACT FROM AUTHOR]

It has recently been suggested that precision oncology studies should be reanalysed using the intention-to-treat (ITT) methodology developed for randomized controlled clinical trials. This reanalysis dramatically decreases response rates in precision medicine studies. We contend that the ITT analysis of precision oncology trials is invalid. The ITT methodology was developed three decades ago to mitigate the problems of randomized trials, which try to ensure that both arms have an unselected patient population free from confounders. In contrast, precision oncology trials specifically select patients for confounders (that is biomarkers) that predict response. To demonstrate the issues inherent in an ITT reanalysis for precision cancer medicine studies, we take as an example the drug larotrectinib (TRK inhibitor) approved because of remarkable responses in malignancies harbouring NTRK fusions. Based on large-scale studies, NTRK fusions are found in ~0.31% of tumours. In a non-randomized pivotal study of larotrectinib, 75% of the 55 treated patients responded. Based upon the prevalence of NTRK fusions, ~18,000 patients would need to be screened to enrol the 55 treated patients. Utilizing the ITT methodology, the revised response rate to larotrectinib would be 0.23%. This is, of course, a dramatic underestimation of the efficacy of this now Food and Drug Administration (FDA)–approved drug. Similar issues can be shown for virtually any biomarker-based precision clinical trial. Therefore, retrofitting the ITT analysis developed for unselected patient populations in randomized trials yields misleading conclusions in precision medicine studies. • Precision cancer medicine uses biomarkers to customize cognate targeted therapies. • Intention-to-treat reduces bias in randomized trials of unselected patients. • Precision medicine trials prescreen patients to find those with the biomarker. • Prescreening may require hundreds of patients to find one with a rare biomarker. • Intention-to-treat analyses that include prescreened patients are unsuitable for precision trials. [ABSTRACT FROM AUTHOR]

Noninferiority clinical trials aim to show an experimental treatment is therapeutically no worse than standard of care, particularly if the new treatment is preferred for reasons such as cost, convenience, safety, and so on. Noninferiority trials are by nature less conservative than superiority studies: protocol violations may increase bias toward the alternative hypothesis of noninferiority. Our objective was to compare multiple imputation, a linear mixed model, and other methods for analyzing a longitudinal trial with missing data in intention-to-treat and per-protocol populations. We simulated trials with missing data and noncompliance due to treatment inefficacy under varying trial conditions (e.g., trajectory of treatment effects, correlation between repeated measures, and missing data mechanism), assessing each approach by estimating bias, Type I error, and power. We found that multiple imputation using auxiliary data on noncompliance in the imputation model performed best. A hybrid intention-to-treat/per-protocol multiple imputation approach with a missing not at random imputation model produced low Type I error, was unbiased and maintained reasonable power to detect noninferiority. We conclude that the anti-conservatism of noninferiority trial estimands conforming with the intention-to-treat principle may be offset by imputation models that include variables on intercurrent events. for this article are available online. [ABSTRACT FROM AUTHOR]

Background: Cluster randomized trials (CRTs) are a design used to test interventions where individual randomization is not appropriate. The mixed model for repeated measures (MMRM) is a popular choice for individually randomized trials with longitudinal continuous outcomes. This model's appeal is due to avoidance of model misspecification and its unbiasedness for data missing completely at random or at random.Methods: We extended the MMRM to cluster randomized trials by adding a random intercept for the cluster and undertook a simulation experiment to investigate statistical properties when data are missing at random. We simulated cluster randomized trial data where the outcome was continuous and measured at baseline and three post-intervention time points. We varied the number of clusters, the cluster size, the intra-cluster correlation, missingness and the data-generation models. We demonstrate the MMRM-CRT with an example of a cluster randomized trial on cardiovascular disease prevention among diabetics.Results: When simulating a treatment effect at the final time point we found that estimates were unbiased when data were complete and when data were missing at random. Variance components were also largely unbiased. When simulating under the null, we found that type I error was largely nominal, although for a few specific cases it was as high as 0.081.Conclusions: Although there have been assertions that this model is inappropriate when there are more than two repeated measures on subjects, we found evidence to the contrary. We conclude that the MMRM for CRTs is a good analytic choice for cluster randomized trials with a continuous outcome measured longitudinally.Trial Registration: ClinicalTrials.gov, ID: NCT02804698. [ABSTRACT FROM AUTHOR]

Promoting engagement in formal volunteering represents a potential means of facilitating healthy aging. Given reluctance to participate in volunteering has been partially attributed to negative perceptions of various aspects of this activity, this study assessed whether trialing volunteering can improve perceptions among older people. Using a parallel-group design, Australians aged 60+ years (n = 445) were randomly assigned to one of two conditions, one in which they were encouraged to trial volunteering and one in which they were asked to continue their usual activities. Perceptions and attitudes among those in the volunteering condition became significantly more favorable over 6 months relative to those in the control condition, with this change predicted by several aspects of the volunteering experience (e.g., acquisition of skills, increased social connectedness). Providing access to roles that cater to the learning and social needs of older adults appears to be important for improving attitudes toward engaging in volunteer work. [ABSTRACT FROM AUTHOR]

Aims: We assessed the problems and efficacy of glecaprevir + pibrentasvir (GLE/PIB) therapy for patients infected with hepatitis C virus (HCV) in the real world. Method: A total of 423 patients infected with HCV who started treatment at eight different centers in Japan were enrolled in the study. Glecaprevir (300 mg) and pibrentasvir (120 mg) were given once daily for 8 weeks to 246 non‐cirrhotic direct‐acting antiviral (DAA)‐naive patients with HCV genotype (GT)‐1 or ‐2, and for 12 weeks to patients who: were DAA‐naive cirrhotic (n = 55), had experienced DAA failure (n = 78), were cirrhotic and had DAA failure (n = 37), and were other GT‐1/2 (n = 7). Anti‐HCV efficacy was defined as a sustained virologic response 12 weeks post‐treatment (SVR12). The evaluation was undertaken in an intention‐to‐treat (ITT) population and in patients who were assessed at SVR12 (modified ITT population). Results: In the ITT population, 220 (89%) patients on the 8‐week regimen and 164 (93%) patients on the 12‐week regimen achieved SVR12. The 30 dropout patients were predominantly men and with GT‐2. All other DAA‐naive GT‐1 patients achieved SVR12. The 12‐week regimen resulted in 100% SVR12 in 41 GT‐2 patients. Nine patients did not achieve SVR12: two DAA naive with GT‐2a, two GT‐3b patients, two GT‐1 patients with discontinuation, and three other GT‐1 patients with a history of DAA failure. Four of seven patients who discontinued treatment due to severe adverse effects were more than 75 years old. Conclusions: Glecaprevir + pibrentasvir had a remarkable anti‐HCV effect in GT‐1 and GT‐2 patients, but not in GT‐3b patients. Although this therapy was reasonably safe, it is necessary to carefully consider elderly and dropout patients. [ABSTRACT FROM AUTHOR]

In this article, I review the key elements of the proposed International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use E9 Addendum, present a constructive critique, and provide recommendations of how it can be improved. To highlight ideas, I present a case study involving a confirmatory trial for a chronic pain medication. [ABSTRACT FROM AUTHOR]

Statistical interpretation of data collected in a randomised controlled trial (RCT) is conducted on the intention‐to‐treat (ITT) and/or the per‐protocol (PP) study populations. ITT analysis is a comparison of treatment groups including all patients as originally allocated after randomisation regardless if treatment was initiated or completed. PP analysis is a comparison of treatment groups including only those patients who completed the treatment as originally allocated, although it is often criticised because of its potential to instil bias. A previous report from an RCT conducted to evaluate the efficacy of dehydrated human amnion/chorion membrane allograft (EpiFix) as an adjunct to standard comprehensive wound therapy consisting of moist dressings and multi‐layer compression in the healing of venous leg ulcers (VLUs) only reported PP study results (n = 109, 52 EpiFix and 57 standard care patients), although there were 128 patients randomised: 64 to the EpiFix group and 64 to the standard care group. Primary study outcome was the incidence of healing at 12 weeks. The purpose of the present study is to report ITT results on all 128 randomised subjects and assess if both ITT and PP data analyses arrive at the same conclusion of the efficacy of EpiFix as a treatment for VLU. Rates of healing for the ITT and PP populations were, respectively, 50% and 60% for those receiving EpiFix and 31% and 35% for those in the standard care cohort. Within both ITT and PP analyses, these differences were statistically significant; P = 0.0473, ITT and P = 0.0128, PP. The Kaplan‐Meier plot of time to heal within 12 weeks for the ITT and PP populations demonstrated a superior wound‐healing trajectory for EpiFix compared with VLUs treated with standard care alone. These data provide clinicians and health policymakers an additional level of assurance regarding the effectiveness of EpiFix. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • The dropout rate is lower for patients listed for liver transplantation with a potential live donor. • The waiting time is shorter for patients listed for liver transplantation with a potential live donor. • These 2 advantages of live donation result in a survival benefit for patients with HCC listed with a potential live donor. Background & Aims There are conflicting reports on the outcomes after live donor liver transplantation in patients with hepatocellular carcinoma (HCC). We aimed to compare the survival of patients with HCC, with a potential live donor (pLDLT) at listing vs. no potential donor (pDDLT), on an intention-to-treat basis. Methods All patients with HCC listed for liver transplantation between 2000–2015 were included. The pLDLT group was comprised of recipients with a potential live donor identified at listing. Patients without a live donor were included in the pDDLT group. Survival was assessed by the Kaplan-Meier method. Multivariable Cox regression was applied to identify potential predictors of mortality. Results A total of 219 patients were included in the pLDLT group and 632 patients in the pDDLT group. In the pLDLT group, 57 patients (26%) were beyond the UCSF criteria whereas 119 patients (19%) in the pDDLT group were beyond (p = 0.02). Time on the waiting list was shorter for the pLDLT than the pDDLT group (4.8 [2.9–8.5] months vs. 6.2 [3.0–12.0] months, respectively, p = 0.02). The dropout rate was 32/219 (14.6%) in the pLDLT and 174/632 (27.5%) in the pDDLT group, p <0.001. The 1-, 3- and 5-year intention-to-treat survival rates were 86%, 72% and 68% in the pLDLT vs. 82%, 63% and 57% in the pDDLT group, p = 0.02. Having a potential live donor was a protective factor for death (hazard ratio [HR] 0.67; 95% CI 0.53–0.86). Waiting times of 9–12 months (HR 1.53; 95% CI 1.02–2.31) and ≥12 months (HR 1.69; 95% CI 1.23–2.32) were predictors of death. Conclusion Having a potential live donor at listing was associated with a significant decrease in the risk of death in patients with HCC in this intention-to-treat analysis. This benefit is related to a lower dropout rate and a shorter waiting period. Lay summary Liver transplantation (LT) offers the best chance of survival for patients with hepatocellular carcinoma and can be performed using grafts from deceased donors or live donors. In this work, we aimed to assess the differences in survival after live donor LT when compared to deceased donor LT. We studied 219 patients listed for live donor LT and 632 patients listed for deceased donor LT. Patients who had a potential live donor at the time of listing had a higher survival rate. Therefore, being listed for a live donor LT was a protective factor against death. [ABSTRACT FROM AUTHOR]

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Abstract Background Intention-to-treat (ITT) analysis is commonly recommended for use, due to its benefits on external validity, in randomized, controlled trials (RCTs). No published reports describe how ITT analysis, as well as alternative approaches, are used in anti-infective RCTs. The purpose of this study is to describe the extent to which ITT analysis and alternative data approaches are used, the practices used to handle missing subject data, and whether non-inferiority trials present both ITT and per protocol (PP) analyses. Results of this analysis will help guide end users of infectious diseases primary drug literature. Methods A cross-sectional study of RCTs of anti-infectives published from January 1, 2013 through December 31, 2014 was conducted. A PubMed search identified relevant articles published in five specialty infectious diseases journals and four general medical journals. Each article was reviewed by two independent investigators with discrepancies resolved by consensus. Descriptive statistics were used to quantify results. Results One hundred four articles met study criteria. The most common medication classes represented in the RCTs were hepatitis C antivirals (26 %), antibacterials (25 %), and antiretrovirals (21 %). Thirty studies (29 %) were non-inferiority trials. Most studies (77 %) described use of ITT or modified ITT (mITT) in their methods. Of the ITT and mITT studies, most (73 %) did not describe practices used to handle missing data. Most (97 %) non-inferiority trials described use of ITT, mITT, or both; however, only 15 (50 %) also described use of PP. Conclusions RCTs of anti-infectives commonly employ ITT and mITT. Most do not describe how missing data were addressed. Non-inferiority trials of anti-infectives do not consistently employ both ITT and PP populations.

Background: The cohort multiple randomized controlled trial (cmRCT) can tackle some of the weaknesses of an RCT which has triggered the interest of researchers considerably over time. Several challenges persist regarding the methods of analyzing such valued data. The paucity of international recommendations concerning the statistical methods for analyzing trial data has led to a variety of strategies further complicating the result comparison. Our aim was to review the different cmRCT analysis methods since cmRCT was first proposed in 2010., Methodology: A search for full-length studies presenting statistical analysis of the data collected adopting a cmRCT design was conducted on PubMed, Cochrane Library, EMBASE, JSTOR, Scopus, MEDLINE, and ClinicalTrials.gov., Results: Out of 186 studies screened, we selected 22 for the full-text screening and 11 were found eligible for data extraction. All 11 studies were conducted in high-income countries, reflecting the design being underutilized in other settings. All of the studies were found to have used intention-to-treat (ITT) analysis with four of them utilizing instrumental variables (IV) analysis or a complier average causal effect (CACE). Randomization was noted often to be interchangeably used for random selection. Sample size calculation was not clearly specified in the majority of the studies., Conclusion: Clarity regarding the distinction between an RCT and a cmRCT is warranted. The fundamental difference in design, which leads to certain biases that need to be taken care of by adopting IV or CACE analysis, has to be understood before taking up a cmRCT., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2024, Narzari et al.)