Economic evaluation of anti-CD19 CAR T-cell pathway for large B-cell lymphomas in the real-life setting: the experience of an Italian hub center in the first three years of activity.

Poor literature report actual and detailed costs of chimeric antigen receptor (CAR) T-cell pathway in a real-life setting. We retrospectively collect data for all patients with relapsed/refractory aggressive large B-cell lymphoma who underwent leukapheresis between August 2019 and August 2022. All costs and medical resource consumption accountability were calculated on an intention-to-treat (ITT) basis, starting from leukapheresis to the time when the patient (infused or not) exited the CAR T-cell pathway for any reason. Eighty patients were addressed to leukapheresis and 59 were finally infused. After excluding CAR-T product cost, the main driver of higher costs were hospitalizations followed by the examinations/procedures and other drugs, respectively 43.9%, 26.3% and 25.4% of the total. Regarding costs of drugs and medications other than CAR T products, the most expensive items are those referred to AEs, both infective and extra-infective within 30 days from infusion, that account for 63% of the total. Density plot of cost analyses did not show any statistically significant difference with respect to the years of leukapheresis or infusion. To achieve finally 59/80 infused patients the per capita patients without CAR-T products results 74,000 euros. This analysis covers a growing concern on health systems, the burden of expenses related to CAR T-cell therapy, which appears to provide significant clinical benefit despite its high cost, thus making economic evaluations highly relevant. The relevance of this study should be also viewed in light of continuously evolving indications for this therapy.

Assessing efficacy in non-inferiority trials with non-adherence to interventions: Are intention-to-treat and per-protocol analyses fit for purpose?

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.

Is Intention to Treat Still the Gold Standard or Should Health Technology Assessment Agencies Embrace a Broader Estimands Framework?: Insights and Perspectives From the National Institute for Health and Care Excellence and Institut für Qualität und Wirtschaftlichkeit im Gesundheitswesen on the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use E9 (R1) Addendum.

OBJECTIVES: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Power and sample sizes estimation in clinical trials with treatment switching in intention-to-treat analysis: a simulation study.

BACKGROUND: Treatment switching, also called crossover, is common in clinical trials because of ethical concerns or other reasons. When it occurs and the primary objective is to identify treatment effects, the most widely used intention-to-treat analysis may lead to underpowered trials. Here, we presented an approach to preview power reductions and to estimate sample sizes required to achieve the desired power when treatment switching occurs in the intention-to-treat analysis. METHODS: We proposed a simulation-based approach and developed an R package to perform power and sample sizes estimation in clinical trials with treatment switching. RESULTS: We simulated a number of randomized trials incorporating treatment switching and investigated the impact of the relative effectiveness of the experimental treatment to the control, the switching probability, the switching time, and the deviation between the assumed and the real distributions for the survival time on power reductions and sample sizes estimation. The switching probability and the switching time are key determinants for significant power decreasing and thus sample sizes surging to maintain the desired power. The sample sizes required in randomized trials absence of treatment switching vary from around four-fifths to one-seventh of the sample sizes required in randomized trials allowing treatment switching as the switching probability increases. The power reductions and sample sizes increase with the decrease of switching time. CONCLUSIONS: The simulation-based approach not only provides a preview for power declining but also calculates the required sample size to achieve an expected power in the intention-to-treat analysis when treatment switching occurs. It will provide researchers and clinicians with useful information before randomized controlled trials are conducted.

Randomized controlled trials of biomarker targets.

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.

Using modified intention-to-treat as a principal stratum estimator for failure to initiate treatment.

BACKGROUND: A common intercurrent event affecting many trials is when some participants do not begin their assigned treatment. For example, in a double-blind drug trial, some participants may not receive any dose of study medication. Many trials use a 'modified intention-to-treat' approach, whereby participants who do not initiate treatment are excluded from the analysis. However, it is not clear (a) the estimand being targeted by such an approach and (b) the assumptions necessary for such an approach to be unbiased. METHODS: Using potential outcome notation, we demonstrate that a modified intention-to-treat analysis which excludes participants who do not begin treatment is estimating a principal stratum estimand (i.e. the treatment effect in the subpopulation of participants who would begin treatment, regardless of which arm they were assigned to). The modified intention-to-treat estimator is unbiased for the principal stratum estimand under the assumption that the intercurrent event is not affected by the assigned treatment arm, that is, participants who initiate treatment in one arm would also do so in the other arm (i.e. if someone began the intervention, they would also have begun the control, and vice versa). RESULTS: We identify two key criteria in determining whether the modified intention-to-treat estimator is likely to be unbiased: first, we must be able to measure the participants in each treatment arm who experience the intercurrent event, and second, the assumption that treatment allocation will not affect whether the participant begins treatment must be reasonable. Most double-blind trials will satisfy these criteria, as the decision to start treatment cannot be influenced by the allocation, and we provide an example of an open-label trial where these criteria are likely to be satisfied as well, implying that a modified intention-to-treat analysis which excludes participants who do not begin treatment is an unbiased estimator for the principal stratum effect in these settings. We also give two examples where these criteria will not be satisfied (one comparing an active intervention vs usual care, where we cannot identify which usual care participants would have initiated the active intervention, and another comparing two active interventions in an unblinded manner, where knowledge of the assigned treatment arm may affect the participant's choice to begin or not), implying that a modified intention-to-treat estimator will be biased in these settings. CONCLUSION: A modified intention-to-treat analysis which excludes participants who do not begin treatment can be an unbiased estimator for the principal stratum estimand. Our framework can help identify when the assumptions for unbiasedness are likely to hold, and thus whether modified intention-to-treat is appropriate or not.

Effect of Baduanjin exercise on cerebral blood flow and cognitive frailty in the community older adults with cognitive frailty: A randomized controlled trial.

Objectives: Regular Baduanjin exercise training has been shown to be beneficial to the physical and cognitive health of older adults, but the underlying mechanisms remain to be investigated. This study examined the influence of Baduanjin on cerebral hemodynamics in community-dwelling older adults with cognitive frailty. Design: Randomized controlled trial. Methods: A total of 102 eligible participants were randomly allocated into the Baduanjin exercise intervention group (BEG) or usual physical activity control group (CG) for 24 weeks. Cerebral hemodynamic parameters of bilateral middle/anterior cerebral artery and basilar artery, cognitive ability and physical frailty were assessed using Transcranial Doppler (TCD), Montreal Cognitive Assessment (MoCA) and Edmonton Frailty Scale (EFS) at baseline and 24 weeks post-intervention. Results: After 24 weeks intervention, the changes in peak systolic velocity (PSV), mean blood flow velocity (MBFV), and end diastolic velocity (EDV) in the right middle cerebral artery and basilar artery were better in the BEG than in the CG; the increase in MoCA scores and the decrease in EFS scores were significantly higher in the BEG than in the CG. Moreover, the interaction of exercise and time on those variables showed obvious significance. Conclusions: The 24 weeks Baduanjin exercise training had a positive beneficial effect on cerebral blood flow in community-dwelling older adults with cognitive frailty. This may be a potential mechanism by which Baduanjin exercise improves the cognitive frailty in older adults. Trial registration: Chinese Clinical Trial Registry, ChiCTR1800020341. Date of registration: December 25, 2018, http://www.chictr.org.cn/showproj.aspx?proj=29846.

Invited Commentary: Conducting and Emulating Trials to Study Effects of Social Interventions.

All else being equal, if we had 1 causal effect we wished to estimate, we would conduct a randomized trial with a protocol that mapped onto that causal question, or we would attempt to emulate that target trial with observational data. However, studying the social determinants of health often means there are not just 1 but several causal contrasts of simultaneous interest and importance, and each of these related but distinct causal questions may have varying degrees of feasibility in conducting trials. With this in mind, we discuss challenges and opportunities that arise when conducting and emulating such trials. We describe designing trials with the simultaneous goals of estimating the intention-to-treat effect, the per-protocol effect, effects of alternative protocols or joint interventions, effects within subgroups, and effects under interference, and we describe ways to make the most of all feasible randomized trials and emulated trials using observational data. Our comments are grounded in the study results of Courtin et al. (Am J Epidemiol. 2022;191(8):1444-1452).

Evaluation of the Swedish school-based program "tobacco-free DUO" in a cluster randomized controlled trial (TOPAS study). Results at 2-year follow-up.

Friends' and parents' tobacco use are strong predictors of tobacco uptake among adolescents, however the effectiveness of interventions based on public commitments and agreements to remain tobacco-free are not established. Here, we evaluated the effectiveness of the school-based Swedish program Tobacco-Free Duo (T-Duo) in preventing adolescents from initiating tobacco use (TOPAS study). T-Duo is a multi-component intervention witha formal agreement between a student and an adult partner to remain tobacco-free during the entire 3-year study period as core component. The standardized educational component of the same program was used as comparator (control). Primary outcome was the probability to "remain a non-user" of i) cigarettes and secondary outcomes ii) other types of tobacco at second (21-month) follow-up. Analysis was conducted according to Intention To Treat. In total 1776 adolescents (51% female) aged 12-13 in grade 7 from 34 participating high schools in Sweden were included at baseline in 2018, of which 1489 were retained after 21 months. The Risk Ratio (RR) of not having tried cigarettes 21-months after initiation of the intervention was 1.03(CI 0.98-1.08), Bayes Factor(BF) = 0.93, Absolute Risk Difference(ARD) = 3.1%. Similar associations were found for never smoked a whole cigarette and never use of other tobacco/nicotine products. There was a minimal reduction of tobacco use initiation among Swedish adolescents assigned to a multi-component intervention (T-Duo) compared to those assigned to standardized classroom education after 2 schoolyears. However, for most outcomes' findings were inconclusive and not reliably different from zero. Trial registration: ISRCTN5285808 (doi:https://doi.org/10.1186/ISRCTN52858080); Study protocol: DERR1-https://doi.org/10.2196/21100. Registration: Current Controlled Trials ISRCTN52858080 Date: January 4, 2019, retrospectively registered. Protocol: Galanti, M.R., Pulkki-Brännström, A.-M., Nilsson, M., 2020. Tobacco-free duo adult-child contract for prevention of tobacco use among adolescents and parents: protocol for a mixed-design evaluation. JMIR Res. Protoc. 9, e21100. doi:10.2196/21100.

Patient Selection for Downstaging of Hepatocellular Carcinoma Prior to Liver Transplantation-Adjusting the Odds?

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.

Clarifying selection bias in cluster randomized trials.

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.

Rethinking intercurrent events in defining estimands for tuberculosis trials.

BACKGROUND/AIMS: Tuberculosis remains one of the leading causes of death from an infectious disease globally. Both choices of outcome definitions and approaches to handling events happening post-randomisation can change the treatment effect being estimated, but these are often inconsistently described, thus inhibiting clear interpretation and comparison across trials. METHODS: Starting from the ICH E9(R1) addendum's definition of an estimand, we use our experience of conducting large Phase III tuberculosis treatment trials and our understanding of the estimand framework to identify the key decisions regarding how different event types are handled in the primary outcome definition, and the important points that should be considered in making such decisions. A key issue is the handling of intercurrent (i.e. post-randomisation) events (ICEs) which affect interpretation of or preclude measurement of the intended final outcome. We consider common ICEs including treatment changes and treatment extension, poor adherence to randomised treatment, re-infection with a new strain of tuberculosis which is different from the original infection, and death. We use two completed tuberculosis trials (REMoxTB and STREAM Stage 1) as illustrative examples. These trials tested non-inferiority of new tuberculosis treatment regimens versus a control regimen. The primary outcome was a binary composite endpoint, 'favourable' or 'unfavourable', which was constructed from several components. RESULTS: We propose the following improvements in handling the above-mentioned ICEs and loss to follow-up (a post-randomisation event that is not in itself an ICE). First, changes to allocated regimens should not necessarily be viewed as an unfavourable outcome; from the patient perspective, the potential harms associated with a change in the regimen should instead be directly quantified. Second, handling poor adherence to randomised treatment using a per-protocol analysis does not necessarily target a clear estimand; instead, it would be desirable to develop ways to estimate the treatment effects more relevant to programmatic settings. Third, re-infection with a new strain of tuberculosis could be handled with different strategies, depending on whether the outcome of interest is the ability to attain culture negativity from infection with any strain of tuberculosis, or specifically the presenting strain of tuberculosis. Fourth, where possible, death could be separated into tuberculosis-related and non-tuberculosis-related and handled using appropriate strategies. Finally, although some losses to follow-up would result in early treatment discontinuation, patients lost to follow-up before the end of the trial should not always be classified as having an unfavourable outcome. Instead, loss to follow-up should be separated from not completing the treatment, which is an ICE and may be considered as an unfavourable outcome. CONCLUSION: The estimand framework clarifies many issues in tuberculosis trials but also challenges trialists to justify and improve their outcome definitions. Future trialists should consider all the above points in defining their outcomes.

The relationship between platelet distribution width and disease activity in patients with polymyositis.

Introduction: Muscle enzymes are an indicator of ongoing muscle damage and disease activity in patients with idiopathic inflammatory myopathy. Although platelet-related parameters have been shown to be useful as markers of disease activity in autoimmune diseases, the relationship between platelet distribution width (PDW) and disease activity has not been previously studied in polymyositis. We aimed to determine the relationship between PDW and disease activity in patients with polymyositis. Material and methods: Twenty-seven patients with polymyositis and thirty healthy controls were included in the study. Disease activity was evaluated using the myositis disease activity assessment Visual Analogue Scale (MYOACT) and the Myositis Intention to Treat Index (MITAX). The relationship between PDW and disease activity was evaluated using Pearson's or Spearman's correlation and reliability was assessed using correlation coefficients. Results: The mean platelet volume (MPV) and plateletcrit (PCT) were significantly higher and PDW was significantly lower in patients with polymyositis compared to the control group. The mean PDW levels were lower in patients with constitutional symptoms and arthralgia/arthritis (p < 0.005). Although PDW levels were lower in patients with mechanical hand, lung involvement, or dysphagia compared to patients without, there was no statistically significant difference between them. Platelet distribution width was found to be negatively correlated with disease activity. Conclusions: We found that PDW was negatively correlated with MYOACT and MITAX, widely used tools in assessing the disease activity of polymyositis. Based on this, PDW may be utilized as a non-invasive potential index to assess disease activity in patients with polymyositis.

Total neoadjuvant FOLFIRINOX versus neoadjuvant gemcitabine-based chemoradiotherapy and adjuvant gemcitabine for resectable and borderline resectable pancreatic cancer (PREOPANC-2 trial): study protocol for a nationwide multicenter randomized controlled trial.

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.

Intention-to-treat analysis may be more conservative than per protocol analysis in antibiotic non-inferiority trials: a systematic review.

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 .

Interpretation of clinical studies in electrophysiology: statistical considerations for the clinician.

Atrial fibrillation (AF) outcome studies play an essential role in the development of clinical evidence to improve the management of AF patients. Understanding the statistical considerations involved in study design and interpretation is crucial if electrophysiologists are to change practice. In this review, with the guidance of a medical statistician and a clinical trialist we provide an overview of important statistical issues for the clinician, with a focus on clinical studies in AF ablation. Various types of study designs including randomized controlled trials, superiority, and non-inferiority studies are described, along with their implications and limitations. Appropriate sample size calculation is fundamental to ensure statistical power and efficient resource use. Multiplicity in study endpoints is useful to encapsulate the varied effects of an intervention/treatment, although statistical adjustments are required to account for this. Finally, we discuss the limitations with the current primary endpoint used in AF ablation studies, namely, freedom from atrial tachyarrhythmia of >30 seconds, and propose AF burden as a more relevant primary endpoint, based on findings from recent clinical studies. However, technical challenges need to be overcome before AF burden can be routinely adopted, especially the need for non-invasive, long-term monitoring. The emergence of newer technologies, particularly wearable technology, offers significant promise in filling this gap.

Long-term efficacy of meaning-centered group psychotherapy for cancer survivors: 2-Year follow-up results of a randomized controlled trial.

OBJECTIVE: Meaning-centered group psychotherapy for cancer survivors (MCGP-CS) is an effective intervention to improve personal meaning, psychological well-being, and depressive symptoms until 6 months after the intervention. In this study, the long-term effects of MCGP-CS (i.e., at 1- and 2-year follow-up) on meaning, psychological well-being and posttraumatic growth were assessed, in comparison to supportive group psychotherapy (SGP) and care as usual (CAU). METHODS: Cancer survivors (n = 170) were randomized into MCGP-CS, SGP, or CAU. Assessments were scheduled at baseline, 1 week, 3 months, 6 months, 1 year, and 2 years postintervention. Outcome measures were the Personal Meaning Profile, Ryff's Scales of Psychological Well-Being (SPWB), the Posttraumatic Growth Inventory, and their subscales. Linear mixed models (LMM) were used and results were both reported on an intention-to-treat (ITT) basis, as well as for intervention completers only. RESULTS: LMM and post hoc analyses with Bonferroni correction revealed that MCGP-CS participants reported more improvement on positive relations (subscale of SPWB) than CAU participants of 2-year postintervention (ITT analysis, Cohen's d = .82). Completers also reported more personal growth (subscale of SPWB) after MCGP-CS than after SGP 1-year postintervention (Cohen's d = .94). No long-term effects were found on the other outcome measures. CONCLUSIONS: In the 2 years after MCGP-CS, the short-term significant effects on personal meaning and most positive effects related to psychological well-being faded. However, MCGP-CS had a long-term positive effect on positive relations with others and on survivors' sense of personal growth. TRIAL REGISTRATION: Netherlands Trial Register: NTR3571.

Adjusting for adherence in randomized trials when adherence is measured as a continuous variable: An application to the Lipid Research Clinics Coronary Primary Prevention Trial.

BACKGROUND: Clinicians and patients may be more interested in per-protocol effect estimates than intention-to-treat effect estimates from randomized trials. However, per-protocol effect estimates may be biased due to insufficient adjustment for prognostic factors that predict adherence. Adjustment for this bias is possible when appropriate methods, such as inverse probability weighting, are used. But, when adherence is measured as a continuous variable, constructing these weights can be challenging. METHODS: In the placebo arm of the Lipid Research Clinics Coronary Primary Prevention Trial, we estimated the 7-year cumulative incidence of coronary heart disease under 100% adherence and 0% adherence to placebo. We used dose-response discrete-hazards models with inverse probability weighting to adjust for pre- and post-randomization covariates. We considered several continuous distributions for constructing the inverse probability weights. RESULTS: The risk difference estimate for 100% adherence compared with 0% adherence ranged from -7.7 to -6.1 percentage points without adjustment for baseline and post-baseline covariates, and ranged from -1.8 to 2.2 percentage points with adjustment using inverse probability weights, depending on the dose-response model and inverse probability weight distribution used. CONCLUSIONS: Methods which appropriately adjust for time-varying post-randomization variables can explain away much of the bias in the "effect" of adherence to placebo. When considering continuous adherence, investigators should consider several models as estimates may be sensitive to the model chosen.

Protocol adherence rates in superiority and noninferiority randomized clinical trials published in high impact medical journals.

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.

Intention to treat and per protocol analysis in clinical trials.

In clinical epidemiology, experimental studies usually take the form of randomized controlled clinical trials (RCTs). The data analysis of an RCT can be performed by using two complementary strategies, that is according to the intention to treat (ITT) principle and the per protocol (PP) analysis. By using the ITT approach, investigators aim to assess the effect of assigning a drug whereas by adopting the PP analysis, researchers investigate the effect of receiving the assigned treatment, as specified in the protocol. Both ITT and PP analyses are essentially valid but they have different scopes and interpretations dependent on the context.