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For the analysis of a time‐to‐event endpoint in a single‐arm or randomized clinical trial it is generally perceived that interpretation of a given estimate of the survival function, or the comparison between two groups, hinges on some quantification of the amount of follow‐up. Typically, a median of some loosely defined quantity is reported. However, whatever median is reported, is typically not answering the question(s) trialists actually have in terms of follow‐up quantification. In this paper, inspired by the estimand framework, we formulate a comprehensive list of relevant scientific questions that trialists have when reporting time‐to‐event data. We illustrate how these questions should be answered, and that reference to an unclearly defined follow‐up quantity is not needed at all. In drug development, key decisions are made based on randomized controlled trials, and we therefore also discuss relevant scientific questions not only when looking at a time‐to‐event endpoint in one group, but also for comparisons. We find that different thinking about some of the relevant scientific questions around follow‐up is required depending on whether a proportional hazards assumption can be made or other patterns of survival functions are anticipated, for example, delayed separation, crossing survival functions, or the potential for cure. We conclude the paper with practical recommendations. [ABSTRACT FROM AUTHOR]

Competing risks data are commonly encountered in randomized clinical trials or observational studies. Ignoring competing risks in survival analysis leads to biased risk estimates and improper conclusions. Often, one of the competing events is of primary interest and the rest competing events are handled as nuisances. These approaches can be inadequate when multiple competing events have important clinical interpretations and thus of equal interest. For example, in COVID‐19 in‐patient treatment trials, the outcomes of COVID‐19 related hospitalization are either death or discharge from hospital, which have completely different clinical implications and are of equal interest, especially during the pandemic. In this paper we develop nonparametric estimation and simultaneous inferential methods for multiple cumulative incidence functions (CIFs) and corresponding restricted mean times. Based on Monte Carlo simulations and a data analysis of COVID‐19 in‐patient treatment clinical trial, we demonstrate that the proposed method provides global insights of the treatment effects across multiple endpoints. [ABSTRACT FROM AUTHOR]

The pattern of the difference between two survival curves we often observe in randomized clinical trials for evaluating immunotherapy is not proportional hazards; the treatment effect typically appears several months after the initiation of the treatment (ie, delayed difference pattern). The commonly used logrank test and hazard ratio estimation approach will be suboptimal concerning testing and estimation for those trials. The long‐term restricted mean survival time (LT‐RMST) approach is a promising alternative for detecting the treatment effect that potentially appears later in the study. A challenge in employing the LT‐RMST approach is that it must specify a lower end of the time window in addition to a truncation time point that the RMST requires. There are several investigations and suggestions regarding the choice of the truncation time point for the RMST. However, little has been investigated to address the choice of the lower end of the time window. In this paper, we propose a flexible LT‐RMST‐based test/estimation approach that does not require users to specify a lower end of the time window. Numerical studies demonstrated that the potential power loss by adopting this flexibility was minimal, compared to the standard LT‐RMST approach using a prespecified lower end of the time window. The proposed method is flexible and can offer higher power than the RMST‐based approach when the delayed treatment effect is expected. Also, it provides a robust estimate of the magnitude of the treatment effect and its confidence interval that corresponds to the test result. [ABSTRACT FROM AUTHOR]

Non‐proportional hazards have been observed in many studies especially in immuno‐oncology clinical trials. Traditional analysis using the combined approach with log‐rank test as the significance test and Cox model for treatment effect estimation becomes questionable as this approach relies heavily on the proportional hazards assumption. Inspired by the MCP‐Mod (multiple comparisons and modeling approach) that has been widely used in dose‐finding studies, we propose a similar approach to handle non‐proportional hazards. Using this approach, efficacy signal is first established by a max‐combo test, after which hazard ratios across time will be estimated using a logically nested splines model. Simulations studies and real‐data examples are used to illustrate the use of this approach. [ABSTRACT FROM AUTHOR]

Aims: To evaluate the time‐varying cardio‐protective effect of glucagon‐like peptide‐1 receptor agonists (GLP‐1RAs) using pooled data from eight contemporary cardiovascular outcome trials using the difference in the restricted mean survival time (ΔRMST) as the effect estimate. Material and Methods: Data from eight multinational cardiovascular outcome randomized controlled trials of GLP‐1RAs for type 2 diabetes mellitus were pooled. Flexible parametric survival models were fit from published Kaplan‐Meier plots. The differences between arms in RMST (ΔRMST) were calculated at 12, 24, 36 and 48 months. ΔRMST values were pooled using an inverse variance‐weighted random‐effects model; heterogeneity was tested with Cochran's Q statistic. The endpoints studied were: three‐point major adverse cardiovascular events (MACE), all‐cause mortality, stroke, cardiovascular mortality and myocardial infarction. Results: We included eight large (3183‐14 752 participants, total = 60 080; median follow‐up range: 1.5 to 5.4 years) GLP‐1RA trials. Among GLP‐1RA recipients, we observed an average delay in three‐point MACE of 0.03, 0.15, 0.37 and 0.63 months at 12, 24, 36 and 48 months, respectively. At 48 months, while cardiovascular mortality was comparable in both arms (pooled ΔRMST 0.163 [−0.112, 0.437]; P = 0.24), overall survival was higher (ΔRMST = 0.261 [0.08‐0.43] months) and stroke was delayed (ΔRMST 0.22 [0.15‐0.33]) in patients receiving GLP‐1RAs. Conclusions: Glucagon‐like peptide‐1 receptor agonists may delay the occurrence of MACE by an average of 0.6 months at 48 months, with meaningfully larger gains in patients with cardiovascular disease. This metric may be easier for clinicians and patients to interpret than hazard ratios, which assume a knowledge of absolute risk in the absence of treatment. [ABSTRACT FROM AUTHOR]

BACKGROUND: The results of 2 studies exploring adjuvant immune checkpoint inhibition (aCPI) in high‐risk muscle‐invasive urothelial cancer have yielded conflicting results. A trial employing placebo as the control arm demonstrated a significant prolongation in disease‐free survival (DFS) whereas a trial employing observation as the control arm (IMvigor010) demonstrated no prolongation in DFS with CPI. Here, the authors aimed to estimate the aCPI benefit and to model the potential impact of informative censoring on trial results. METHODS: Survival data from 1518 patients was reconstructed from Kaplan‐Meier curves. A network meta‐analysis approach was used to estimate aCPI benefit through the restricted mean disease‐free survival time (RMDFST). To estimate the potential impact of informative censoring on IMvigor010, a simulation was performed. The minimum proportion of informative censoring on the observation arm that could account for the lack of observed improvement in DFS was estimated. Random variability from the time of censoring to progression was modeled using the exponential distribution. RESULTS: Patients receiving aCPI had better DFS: ΔRMDFST at 36 months of 2.2 (95% CI, 0.6‐3.7, P =.006) months relative to observation/placebo. In IMvigor010, in the observation arm, 20.5% of patients were censored due to consent withdrawal, protocol violation and/or noncompliance, or lost to follow‐up versus 8.2% in the treatment arm. On simulation, it was found that the lack of observed improvement in DFS could have resulted from as few as 14% of the censored patients on observation arm not being censored at random (simulated DFS with 14% informative censoring hazard ratio, 0.83; 95% CI, 0.69‐0.99; P =.049). CONCLUSIONS: Phase 3 trials comparing adjuvant therapies to observation are at risk for informative censoring that could potentially impact interpretation of study results.; By relying on reconstructed survival data from 2 studies on adjuvant immunotherapy for high‐risk urothelial cancer, the authors show that phase 3 trials comparing adjuvant therapies to observation are at risk for informative censoring that could potentially impact interpretation of study results. [ABSTRACT FROM AUTHOR]

Vadadustat is a hypoxia‐inducible factor prolyl‐hydroxylase inhibitor being developed for the treatment of anemia in patients with chronic kidney disease. Sequelae of chronic kidney disease include hyperphosphatemia and anemia, which are frequently treated with phosphate binders and iron supplements, respectively. Two studies evaluating the pharmacokinetics, safety, and tolerability of a single oral dose of vadadustat coadministered with a phosphate binder or iron supplement were conducted in healthy adult participants. In study 1, 54 healthy women and men were administered vadadustat (300 mg) alone and 1 hour before, concurrently with, or 2 hours after a phosphate binder (sevelamer carbonate 1600 mg, calcium acetate 1334 mg, or ferric citrate 2000 mg). In study 2, 10 healthy men were administered vadadustat (450 mg) alone and concomitantly with the oral iron supplement ferrous sulfate (325 mg [equivalent to 65 mg of elemental iron]). Vadadustat exposure was reduced by coadministration with sevelamer carbonate, calcium acetate, ferric citrate, or ferrous sulfate. Geometric least squares mean ratios for area under the concentration‐time curve from time 0 to infinity were reduced 37% to 55% by phosphate binders and 46% by ferrous sulfate. However, when vadadustat was administered 1 hour before phosphate binders, 90% confidence intervals for vadadustat exposure were within the no‐effect boundaries of +50% to –33%, indicating that drug‐drug interactions can be reduced by administering vadadustat 1 hour before phosphate binders. Vadadustat was well tolerated when administered in conjunction with phosphate binders or an iron supplement. [ABSTRACT FROM AUTHOR]

Restricted mean survival time (RMST) is one measure now used to summarize time‐to‐event type data, but it has been pointed out that the distribution of differences in RMST deviates markedly from a normal distribution for controlled clinical trials with small sample sizes. Therefore, we conducted a numerical simulation of the RMST in which the one‐sample survival time follows a Weibull distribution, comparing eight different confidence intervals combining two types of variance with four types of variable transformations, including no transformation. The evaluation items were the coverage probability and the above and below error probabilities for the true value. The variance types were based on Greenwood's formula and its Kaplan–Meier correction. The arcsine square root transformation, logit transformation, and complementary log–log transformation were used as the variable transformations. When the sample size was small and the event rate was low, the confidence interval of the untransformed RMST tended to have a small coverage probability and to be overestimated. Variance by Kaplan–Meier correction improved the coverage. The problems of coverage and overestimation were also improved by variable transformations, and in particular, applying the logit transformation and the complementary log–log transformation both resulted in substantial improvements. Our study suggested that it is preferable to construct the confidence intervals of RMST using the logit transformation for variances based on Greenwood's formula in small sample size trials. The SAS code to replicate the analyses is available at https://github.com/HiroyaHashimoto/SAS-Programs. [ABSTRACT FROM AUTHOR]

Background: Despite low‐density lipoprotein cholesterol‐lowering therapies and other standard‐of‐care therapy, there remains a substantial residual atherosclerotic risk among patients with an acute coronary syndrome (ACS). This study aims to estimate the risk of early and late recurrent major adverse cardiovascular events (MACE) and address its implications on trial design. Methods: A literature search was performed to collect phase III interventional trials on high‐risk ACS patients. Pooled event rates at 90 and 360 days were estimated by fitting random‐effects models using the DerSimonian–Laird method. Under the assumption of a total sample size of 10,000 and 1:1 allocation at a one‐sided alpha of 0.025 using the log‐rank test, the relationship between power and relative risk reduction (RRR) or absolute risk reduction (ARR) was explored for early versus late MACE endpoint. Results: Seven trials representing 82,727 recent ACS patients were analyzed. The pooled rates of recurrent MACE were 4.1% and 8.3% at 90 and 360 days. Approximately 49% of events occurred within the first 90 days. Based on the estimated risks at 90 and 360 days, to attain 90% statistical power, a lower magnitude of RRR is required for late MACE than early MACE (22% vs. 30%), whereas a lower magnitude of ARR is required for early MACE than late MACE (1.2% vs. 1.8%). Conclusion: The initial 90‐day window after ACS represents a vulnerable period for recurrent events. From a trial design perspective, determining a clinically important benefit by RRR versus ARR may influence the decision between early and late MACE as the study endpoint. [ABSTRACT FROM AUTHOR]

We summarize extensions to the analysis of restricted mean survival time (RMST) in the context of time‐to‐event outcomes. The RMST estimate and its inference are based on the classical Kaplan–Meier curves. When covariate effects are considered, an adjusted RMST (ARMST) estimate can be derived analogously based on adjusted Kaplan–Meier curves. The adjusted Kaplan–Meier Estimator (AKME) was developed to reduce confounding by the method of inverse probability of treatment weighting. We will show how the ARMST method combines the concepts of the RMST and AKME to make inferences. Two regression based methods to adjust for potential covariate effect on the RMST estimates will be compared with the ARMST approach. Simulation studies are performed to compare the different methods with and without covariate adjustments. In addition, we will summarize the extension of RMST and ARMST to the setting with competing risks. The restricted mean time lost (RMTL) and adjusted RMTL (ARMTL) are estimates of interest from cumulative incidence curves. A phase 3 oncology clinical trial example is provided to demonstrate the applications of these methods. [ABSTRACT FROM AUTHOR]

Recent years have seen a marked increase in the occurrence of sulfoximines in the chemical sciences, often presented as valuable motifs for medicinal chemistry. This has been prompted by both pioneering works taking sulfoximine containing compounds into clinical trials and the concurrent development of powerful synthetic methods. This review covers recent developments in the synthesis of sulfoximines concentrating on developments since 2015. This includes extensive developments in both S−N and S−C bond formations. Flow chemistry processes for sulfoximine synthesis are also covered. Finally, subsequent transformations of sulfoximines, particularly in N‐functionalization are reviewed, including N−S, N−P, N−C bond forming processes and cyclization reactions. [ABSTRACT FROM AUTHOR]

Randomized clinical trials are often designed to assess whether a test treatment prolongs survival relative to a control treatment. Increased patient heterogeneity, while desirable for generalizability of results, can weaken the ability of common statistical approaches to detect treatment differences, potentially hampering the regulatory approval of safe and efficacious therapies. A novel solution to this problem is proposed. A list of baseline covariates that have the potential to be prognostic for survival under either treatment is pre‐specified in the analysis plan. At the analysis stage, using all observed survival times but blinded to patient‐level treatment assignment, "noise" covariates are removed with elastic net Cox regression. The shortened covariate list is used by a conditional inference tree algorithm to segment the heterogeneous trial population into subpopulations of prognostically homogeneous patients (risk strata). After patient‐level treatment unblinding, a treatment comparison is done within each formed risk stratum and stratum‐level results are combined for overall statistical inference. The impressive power‐boosting performance of our proposed 5‐step stratified testing and amalgamation routine (5‐STAR), relative to that of the logrank test and other common approaches that do not leverage inherently structured patient heterogeneity, is illustrated using a hypothetical and two real datasets along with simulation results. Furthermore, the importance of reporting stratum‐level comparative treatment effects (time ratios from accelerated failure time model fits in conjunction with model averaging and, as needed, hazard ratios from Cox proportional hazard model fits) is highlighted as a potential enabler of personalized medicine. An R package is available at https://github.com/rmarceauwest/fiveSTAR. [ABSTRACT FROM AUTHOR]

Restricted mean survival time (RMST) evaluates the mean event-free survival time up to a prespecified time point. It has been used as an alternative measure of treatment effect owing to its model-free structure and clinically meaningful interpretation of treatment benefit for right-censored data. In clinical trials, another type of censoring called interval censoring may occur if subjects are examined at several discrete time points and the survival time falls into an interval rather than being exactly observed. The missingness of exact observations under interval-censored cases makes the nonparametric measure of treatment effect more challenging. Employing the linear smoothing technique to overcome the ambiguity, we propose a new model-free measure for the interval-censored RMST. As an alternative to the commonly used log-rank test, we further construct a hypothesis testing procedure to assess the survival difference between two groups. Simulation studies show that the bias of our proposed interval-censored RMST estimator is negligible and the testing procedure delivers promising performance in detecting between-group difference with regard to size and power under various configurations of survival curves. The proposed method is illustrated by reanalyzing two real datasets containing interval-censored observations. [ABSTRACT FROM AUTHOR]

Between-group comparison based on the restricted mean survival time (RMST) is getting attention as an alternative to the conventional logrank/hazard ratio approach for time-to-event outcomes in randomized controlled trials (RCTs). The validity of the commonly used nonparametric inference procedure for RMST has been well supported by large sample theories. However, we sometimes encounter cases with a small sample size in practice, where we cannot rely on the large sample properties. Generally, the permutation approach can be useful to handle these situations in RCTs. However, a numerical issue arises when implementing permutation tests for difference or ratio of RMST from two groups. In this article, we discuss the numerical issue and consider six permutation methods for comparing survival time distributions between two groups using RMST in RCTs setting. We conducted extensive numerical studies and assessed type I error rates of these methods. Our numerical studies demonstrated that the inflation of the type I error rate of the asymptotic methods is not negligible when sample size is small, and that all of the six permutation methods are workable solutions. Although some permutation methods became a little conservative, no remarkable inflation of the type I error rates were observed. We recommend using permutation tests instead of the asymptotic tests, especially when the sample size is less than 50 per arm. [ABSTRACT FROM AUTHOR]

Summary: The design of a clinical trial is often complicated by the multi‐systemic nature of the disease; a single endpoint often cannot capture the spectrum of potential therapeutic benefits. Multi‐domain outcomes which take into account patient heterogeneity of disease presentation through measurements of multiple symptom/functional domains are an attractive alternative to a single endpoint. A multi‐domain test with adaptive weights is proposed to synthesize the evidence of treatment efficacy over numerous disease domains. The test is a weighted sum of domain‐specific test statistics with weights selected adaptively via a data‐driven algorithm. The null distribution of the test statistic is constructed empirically through resampling and does not require estimation of the covariance structure of domain‐specific test statistics. Simulations show that the proposed test controls the type I error rate, and has increased power over other methods such as the O'Brien and Wei‐Lachin tests in scenarios reflective of clinical trial settings. Data from a clinical trial in a rare lysosomal storage disorder were used to illustrate the properties of the proposed test. As a strategy of combining marginal test statistics, the proposed test is flexible and readily applicable to a variety of clinical trial scenarios. [ABSTRACT FROM AUTHOR]

Randomized controlled trials are the gold standard to investigate efficacy and safety of new treatments. In certain settings, however, randomizing patients to control may be difficult for ethical or feasibility reasons. Borrowing strength using relevant individual patient data on control from external trials or real‐world data (RWD) sources may then allow us to reduce, or even eliminate, the concurrent control group. Naive direct use of external control data is not valid due to differences in patient characteristics and other confounding factors. Instead, we suggest the rigorous application of meta‐analytic and propensity score methods to use external controls in a principled way. We illustrate these methods with two case studies: (i) a single‐arm trial in a rare cancer disease, using propensity score matching to construct an external control from RWD; (ii) a randomized trial in children with multiple sclerosis, borrowing strength from past trials using a Bayesian meta‐analytic approach. [ABSTRACT FROM AUTHOR]

Background: Body mass index (BMI) is used to define obesity, but it is an imperfect measure of body composition. In the current study, the authors explored the association between types of fat and survival in patients treated with immunotherapy.Methods: A retrospective analysis of 90 patients who were treated with immunotherapy on phase 1 clinical trials at the Winship Cancer Institute in Atlanta, Georgia, from 2009 through 2017 was performed. Overall survival (OS) and progression-free survival (PFS) were used to measure clinical outcomes. Baseline BMI and radiographic images at the middle of the third lumbar vertebrae were obtained. Fat densities were calculated and converted to indices (subcutaneous fat index [SFI], intermuscular fat index [IFI], and visceral fat index [VFI]) after dividing by height in meters squared. Risk groups were created using recursive partitioning and the regression trees method for SFI and IFI, which were selected by stepwise variable selection among all fat-related variables. The Cox proportional hazards model and Kaplan-Meier method were used for the association with OS and PFS.Results: The majority of patients (59%) were male and diagnosed with melanoma (33%) or gastrointestinal cancers (22%). The median BMI was 27.4 kg/m2 , the median SFI was 62.78, the median IFI was 4.06, and the median VFI was 40.53. Low-risk patients (those with an SFI ≥73) had a significantly longer OS (hazard ratio, 0.20; 95% CI, 0.09-0.46 [P < .001]) and PFS (hazard ratio, 0.38; 95% CI, 0.20-0.72 [P = .003]) compared with patients at intermediate risk (those with an SFI <73 and IFI <3.4) and poor risk (those with an SFI <73 and IFI ≥3.4). The Uno concordance statistics were found to be higher for fat risk groups than BMI in predicting OS (0.603 vs 0.574; P = .581) and PFS (0.602 vs 0.586; P = .71).Conclusions: Increased BMI, increased SFI, and decreased IFI may be associated with prolonged survival in patients with cancer who are treated with immunotherapy. Further studies are needed to elucidate the effect of adiposity on the host immune response to immunotherapy. [ABSTRACT FROM AUTHOR]

The hazard ratio is widely used to measure or to summarize the magnitude of treatment effects, but it is justifiably difficult to interpret in a meaningful way to patients and perhaps for clinicians as well. In addition, it is most meaningful when the hazard functions are approximately proportional over time. We propose a new measure, termed personalized chance of longer survival. The measure, which quantifies the probability of living longer with one treatment over the another, accounts for individualized characteristics to directly address personalized treatment effects. Hence, the measure is patient focused, which can be used to evaluate subgroups easily. We believe it is intuitive to understand and clinically interpretable in the presence of nonproportionality. Furthermore, because it estimates the probability of living longer by some fixed amount of time, it encodes the probabilistic part of treatment effect estimation. We provide nonparametric estimation and inference procedures that can accommodate censored survival outcomes. We conduct extensive simulation studies, which characterize performance of the proposed method, and data from a large randomized Phase III clinical trial (SWOG S0819) are analyzed using the proposed method. [ABSTRACT FROM AUTHOR]

Aims: Lung ultrasound (LUS) is a useful tool with which to assess subclinical pulmonary congestion and to stratify the prognosis of patients with heart failure (HF). The aim of this study was to evaluate whether an LUS-guided follow-up protocol improves the outcomes of patients with HF.Methods and Results: In this single-blind clinical trial, 123 patients admitted for HF were randomized to either a standard follow-up (n = 62, control group) or a LUS-guided follow-up (n = 61, LUS group). The primary endpoint was a composite of urgent visit, hospitalization for worsening HF and death during follow-up. Visits were scheduled at 14, 30, 90 and 180 days after discharge. Treating physicians were encouraged to modify diuretic therapy in accordance with the number of B-lines recorded by LUS. The mean ± standard deviation (SD) age of the patients was 69 ± 12 years and 72% were male. The mean ± SD left ventricular ejection fraction was 39 ± 14%. The hazard ratio for the primary outcome in the LUS group was 0.518 [95% confidence interval (CI) 0.268-0.998; P = 0.049], mainly resulting from a decrease in the number of urgent visits for worsening HF. The number of patients needed to treat to avoid an event was 5 (95% CI 3-62). Other secondary endpoints such as N-terminal pro-B-type natriuretic peptide reduction were not achieved. The safety parameters were similar in the two groups. Patients in the LUS group received more loop diuretics [51 (91%) vs. 42 (75%); P = 0.02] and showed an improvement in the distance achieved in the 6-min walking test [60 m (interquartile range: 29-125 m) vs. 37 m (interquartile range: 5-70 m); P = 0.023].Conclusions: Tailored LUS-guided diuretic treatment of pulmonary congestion in this proof-of-concept study reduced the number of decompensations and improved walking capacity in patients with HF. LUS is a non-invasive, safe and easy-to-use technique with potential clinical applicability to guide pulmonary congestion treatment in patients with HF. [ABSTRACT FROM AUTHOR]

Immunotherapy—treatments that enlist the immune system to battle tumors—has received widespread attention in cancer research. Due to its unique features and mechanisms for treating cancer, immunotherapy requires novel clinical trial designs. We propose a Bayesian seamless phase I/II randomized design for immunotherapy trials (SPIRIT) to find the optimal biological dose (OBD) defined in terms of the restricted mean survival time. We jointly model progression‐free survival and the immune response. Progression‐free survival is used as the primary endpoint to determine the OBD, and the immune response is used as an ancillary endpoint to quickly screen out futile doses. Toxicity is monitored throughout the trial. The design consists of two seamlessly connected stages. The first stage identifies a set of safe doses. The second stage adaptively randomizes patients to the safe doses identified and uses their progression‐free survival and immune response to find the OBD. The simulation study shows that the SPIRIT has desirable operating characteristics and outperforms the conventional design. [ABSTRACT FROM AUTHOR]

With the emergence of novel therapies exhibiting distinct mechanisms of action compared to traditional treatments, departure from the proportional hazard (PH) assumption in clinical trials with a time-to-event end point is increasingly common. In these situations, the hazard ratiomay not be a valid statistical measurement of treatment effect, and the log-rank test may no longer be the most powerful statistical test. The restricted mean survival time (RMST) is an alternative robust and clinically interpretable summary measure that does not rely on the PH assumption. We conduct extensive simulations to evaluate the performance and operating characteristics of the RMST-based inference and against the hazard ratio-based inference, under various scenarios and design parameter setups. The log-rank test is generally a powerful test when there is evident separation favoring 1 treatment arm at most of the time points across the Kaplan-Meier survival curves, but the performance of the RMST test is similar. Under non-PH scenarioswhere late separation of survival curves is observed, the RMST-based test has better performance than the log-rank test when the truncation time is reasonably close to the tail of the observed curves. Furthermore, when flat survival tail (or low event rate) in the experimental arm is expected, selecting the minimum of the maximum observed event time as the truncation timepoint for the RMST is not recommended. In addition, we recommend the inclusion of analysis based on the RMST curve over the truncation time in clinical settings where there is suspicion of substantial departure from the PH assumption. [ABSTRACT FROM AUTHOR]

Background: Approximately 10% of pancreatic adenocarcinoma (PC) cases are attributed to hereditary causes. Individuals with PC and a personal history of another cancer associated with hereditary breast and ovarian cancer (HBOC) or Lynch syndrome (LS) may be more likely to carry germline mutations.Methods: Participants with PC and a history of cancer were selected from a pancreatic disease registry. Of 1296 individuals with PC, 149 had a relevant history of cancer. If banked DNA was available, a multigene panel was performed for individuals who had not 1) previously had a mutation identified through clinical testing or 2) undergone clinical multigene panel testing with no mutations detected.Results: Twenty-two of 124 individuals with PC and another HBOC- or LS-related cancer who underwent genetic testing had a mutation identified in a PC susceptibility gene (18%). If prostate cancer is excluded, the mutation prevalence increased to 23% (21/93). Mutation carriers were more likely to have more than 1 previous cancer diagnosis (P = .001), to have had clinical genetic testing (P = .001), and to meet National Comprehensive Cancer Network (NCCN) genetic testing criteria (P < .001). Approximately 23% of mutation carriers did not meet NCCN HBOC or LS testing guidelines based on their personal cancer history and reported cancer history in first-degree relatives.Conclusion: At least 18% of individuals with PC and a personal history of other HBOC- or LS-related cancers carry mutations in a PC susceptibility gene based on our data, suggesting that criteria for genetic testing in individuals with PC should include consideration of previous cancer history. Cancer 2018;124:1691-700. © 2018 American Cancer Society. [ABSTRACT FROM AUTHOR]

For clinical trials with time‐to‐event as the primary endpoint, the clinical cutoff is often event‐driven and the log‐rank test is the most commonly used statistical method for evaluating treatment effect. However, this method relies on the proportional hazards assumption in that it has the maximal power in this circumstance. In certain disease areas or populations, some patients can be curable and never experience the events despite a long follow‐up. The event accumulation may dry out after a certain period of follow‐up and the treatment effect could be reflected as the combination of improvement of cure rate and the delay of events for those uncurable patients. Study power depends on both cure rate improvement and hazard reduction. In this paper, we illustrate these practical issues using simulation studies and explore sample size recommendations, alternative ways for clinical cutoffs, and efficient testing methods with the highest study power possible. [ABSTRACT FROM AUTHOR]

It is very challenging to estimate the comparative treatment effect between a treatment therapy and a control therapy on overall survival in the presence of treatment crossover, switch to an alternative non-study therapy, and non-random patient dropout. Existing methods (e.g., intent-to-treat and per-protocol) are known to be biased. We proposed two new estimators to address these analytical challenges and evaluated their performance via a comprehensive simulation study. The new estimators were constructed by combining an enhanced rank-preserving structural failure time model and the inverse probability censoring weighting approach. In the simulation study, we assessed and compared the performance of the two new estimators with four estimators from existing methods. The simulation results show that the new estimators have much better performance in almost all considered settings compared with the existing estimators. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Background and purpose A strong association between time to generalization ( TTG), considered as the time of spreading of the clinical signs from spinal or bulbar localization to both, and survival was recently identified in patients with amyotrophic lateral sclerosis ( ALS). Thus, TTG may be used as an early to intermediate end-point in survival studies. The aim of the present study was to test TTG as a predictor of survival in ALS. Methods This was an observational retrospective study of ALS patients from a tertiary referral centre over a 5-year follow-up period. Results In 212 ALS patients, TTG was associated with time to death/tracheostomy [R 0.62, 95% confidence interval ( CI) 0.53-0.70; P < 0.001]. In a time-to-event analysis, longer TTG resulted in lower risk to reach a composite outcome (death or tracheostomy) both in univariate [hazard ratio ( HR) 0.98, 95% CI 0.97-0.99] and multivariate Cox analyses ( HR 0.98, 95% CI 0.96-0.99). TTG predicted death/tracheostomy at 4 years ( C-statistic 0.58; 95% CI 0.53-0.63) and at 5 years ( C-statistic 0.58; 95% CI 0.53-0.62). Conclusions Based on the present results from a large clinical cohort, TTG may be used as a new early to intermediate end-point to describe the ALS natural history. TTG may be potentially useful as a new primary outcome measure for clinical trials. [ABSTRACT FROM AUTHOR]

In tailored drug development, the patient population is thought of as a mixture of two or more subgroups that may derive differential treatment efficacy. To find the right patient population for the drug to target, it is necessary to infer treatment efficacy in subgroups and combinations of subgroups. A fundamental consideration in this inference process is that the logical relationships between treatment efficacy in subgroups and their combinations should be respected (for otherwise the assessment of treatment efficacy may become paradoxical). We show that some commonly used efficacy measures are not suitable for a mixture population. We also show that the current practice of over-simply extending the least squares means concept when estimating the efficacy in a mixture population is inappropriate. Proposing a new principle called subgroup mixable estimation, we establish the logical relationships among parameters that represent efficacy and develop a simultaneous inference procedure to confidently infer efficacy in subgroups and their combinations. Using oncology studies with time-to-event outcomes as an example, we show that the hazard ratio is not suitable for measuring treatment efficacy in a mixture population and provide appropriate efficacy measures with a rigorous inference procedure. [ABSTRACT FROM AUTHOR]

Aims: A longitudinal and comprehensive analysis of health-related quality of life (HRQOL) was performed during hospitalization for heart failure (HF) or soon after discharge.Methods and Results: A post-hoc analysis was performed of the ASCEND-HF trial. The EuroQOL five dimensions questionnaire (EQ-5D) was administered to study participants at baseline, 24 h, discharge/day 10, and day 30. EQ-5D includes functional dimensions mapped to corresponding utility scores (i.e. 0 = death and 1 = perfect health), and a visual analogue scale (VAS) ranging from 0 (i.e. 'worst imaginable health state') to 100 (i.e. 'best imaginable health state'). The association between baseline and discharge EQ-5D measurements and subsequent clinical outcomes including death and rehospitalization were assessed using multivariable logistic regression and Cox proportional hazards regression. A total of 6943 patients (97%) had complete EQ-5D data at baseline. Mapped utility and VAS scores (mean ± SD) increased over time, respectively, from 0.56 ± 0.23 and 45 ± 22 at baseline to 0.67 ± 0.26 and 58 ± 22 at 24 h and to 0.79 ± 0.20 and 68 ± 22 at discharge, and remained stable at day 30. Lower mapped utility scores at baseline [odds ratio (OR) per 0.1 decrease in utility score 1.03, 95% confidence interval (CI) 1.00-1.06] and discharge (OR 1.10, 95% CI 1.05-1.15) and VAS scores at baseline (OR per 10 point decrease 1.05, 95% CI 1.01-1.09) were significantly associated with increased risk of 30-day all-cause death or HF rehospitalization.Conclusions: Patients hospitalized for HF had severely impaired health status at baseline and, although this improved substantially during admission, health status remained abnormal at discharge. [ABSTRACT FROM AUTHOR]

Background We previously showed that zonisamide significantly improved parkinsonian symptoms by a multicenter, double-blind clinical trial. Aim To confirm the efficacy of zonisamide on Parkinson's disease, a phase 3, randomized, placebo-controlled, multicenter, double-blind trial was carried out in Japan. Methods Participants had advanced Parkinson's disease taking L-dopa with at least one other antiparkinson drug, but were developing a deterioration of response to L-dopa therapy. The trial consisted of a 2-week initial phase (single-blind, with administration of placebo) and a 12-week treatment phase (double-blind, with patients randomly assigned to either placebo, or zonisamide 25 or 50 mg/day). Patients were evaluated using the Unified Parkinson's Disease Rating Scale (UPDRS). Results A total of 185 patients (mean age 64.8 years; mean duration 7.5 years) were included in the efficacy analysis (placebo, zonisamide 25 mg, 50 mg; 63, 61, 61 patients, respectively). When compared with the placebo group, the UPDRS Part III total score at final assessment (the primary end-point for efficacy) significantly improved ( P = 0.029) in the zonisamide 25 mg group. After 12 weeks of therapy, the UPDRS Part III total score significantly improved in both the zonisamide 25 mg ( P = 0.038) and 50 mg groups ( P = 0.049), compared with the placebo group. Neither the zonisamide 25 mg nor 50 mg group differed significantly from the placebo group in the incidence of adverse events ( P = 0.363 and P = 0.713, respectively). Conclusion These findings confirmed that zonisamide is well tolerated and efficacious in the treatment of advanced Parkinson's disease. [ABSTRACT FROM AUTHOR]

Background Little is known about single administration of zonisamide in Parkinson's disease patients. Aim We aimed to evaluate the therapeutic effects of zonisamide monotherapy in early Parkinson's disease patients. Methods A total of 10 untreated ( de novo) patients with Yahr stage I or II participated. Zonisamide was given at a daily dose of 25 mg for 1 month and increased to 50 mg for the next 2 months. Unified Parkinson's Disease Rating Scale parts I- IV and tremor-related Unified Parkinson's Disease Rating Scale (items 16, 20 and 21) were examined every month. Serum zonisamide concentrations and urinary homovanillic acid concentrations were measured. Three patients had rapid eye movement sleep behavior disorder. Sleep condition was asked to patients? spouses. Results At 1 month after zonisamide treatment, Unified Parkinson's Disease Rating Scale scores did not differ from the baseline scores statistically. At 2 and 3 months after zonisamide treatment, Unified Parkinson's Disease Rating Scale part III and tremor-related scores were reduced significantly compared with pretreatment ( P < 0.01). Sleep state improved markedly in three patients with rapid eye movement sleep behavior disorder at 1-2 months after zonisamide treatment. The mean serum concentrations of zonisamide (standard deviation) were 2.0 μg/mL (0.9) at 25 mg/day and 6.6 μg/mL (2.3) at 50 mg/day. Urinary homovanillic acid concentrations were not altered before and after zonisamide administration. Conclusions The present study showed that zonisamide monotherapy improved motor and sleep dysfunction in de novo patients with early Parkinson's disease. Significant therapeutic benefits were present within 1-2 months. Finally, the data highlight a therapeutic potential of zonisamide monotherapy in tremor-predominant patients with early Parkinson's disease. [ABSTRACT FROM AUTHOR]

Event-related potentials ( ERPs) have been proposed as biomarkers capable of reflecting individual differences in neural processing not necessarily detectable at the behavioral level. However, the role of ERPs in developmental research could be hampered by current methodological approaches to quantification. ERPs are extracted as an average waveform over many trials; however, actual amplitudes would be misrepresented by an average if there was high trial-to-trial variability in signal latency. Low signal temporal consistency is thought to be a characteristic of immature neural systems, although consistency is not routinely measured in ERP research. The present study examined the differential contributions of signal strength and temporal consistency across trials in the error-related negativity ( ERN) in 6-year-old children, as well as the developmental changes that occur in these measures. The 234 children were assessed annually in kindergarten, 1st, and 2nd grade. At all assessments signal strength and temporal consistency were highly correlated with the average ERN amplitude, and were not correlated with each other. Consistent with previous findings, ERN deflections in the averaged waveform increased with age. This was found to be a function of developmental increases in signal temporal consistency, whereas signal strength showed a significant decline across this time period. In addition, average ERN amplitudes showed low-to-moderate stability across the three assessments whereas signal strength was highly stable. In contrast, signal temporal consistency did not evidence rank-order stability across these ages. Signal strength appears to reflect a stable individual trait whereas developmental changes in temporal consistency may be experientially influenced. [ABSTRACT FROM AUTHOR]

In this issue of Cancer, Castonguay et al highlight problems with reliably estimating the median OS in the control arm of clinical trials in ovarian cancer. This suggests that more careful reflection is generally required concerning how clinically relevant differences are determined and highlights further issues with the selection of overall survival as a primary endpoint. The article also raises questions regarding the prevalent standard statistical approach used to design and analyze studies with time to event outcomes. [ABSTRACT FROM AUTHOR]

Symptom relief in functional gastrointestinal disorders ( FGID) is frequently sought with complementary and alternative medicine, and various herbal medicine compounds are popular in different parts of the world. Only a few products, however, are standardized and are backed by scientific evidence. This review mainly focuses on mechanistic and clinical data in support of the Japanese traditional compound Rikkunshi-to ( RKT) and of STW-5. Their effects on gut sensori-motor function, neurohormonal network, and controlled clinical data in FGID are revised. RKT and STW-5 appear to possess some degree of gastroprokinetic, visceral analgesic properties, and seem to increase the gastric accommodation response. Controlled trials of RKT and STW-5 support at least a modest effect on symptoms of functional dyspepsia and irritable bowel syndrome, with low side effects profile. With the widespread use of herbals and the relative paucity of effective pharmacological options for FGID, rigorous studies to further elucidate pharmacological actions and clinical applications of herbal compounds are a priority. [ABSTRACT FROM AUTHOR]

BACKGROUND Predicting life expectancy (LE) in patients with metastatic cancer who are receiving palliative therapies is a difficult task. The purpose of the current study was to develop a LE prediction model among patients receiving palliative radiotherapy (RT) that identifies those patients with short (< 3 months) and long (> 1 year) LEs. METHODS The records of 862 patients with metastatic cancer receiving palliative RT at the Dana-Farber/Brigham and Women's Cancer Center between June 2008 and July 2011 were retrospectively reviewed. Cox proportional hazards models were used to evaluate established and potential clinical predictors of LE to construct a model predicting LE of < 3 months and > 1 year. RESULTS The median survival was 5.6 months. On multivariate analysis, factors found to be significantly associated with a shorter LE were cancer type (lung and other vs breast and prostate), older age (> 60 years vs ≤ 60 years), liver metastases, Eastern Cooperative Oncology Group performance status (2-4 vs 0-1), hospitalizations within 3 months before palliative RT (0 vs ≥ 1), and prior palliative chemotherapy courses (≥ 2 vs 0-1). Patients were divided into 3 groups with distinct median survivals: group A (those with 0-1 risk factors), 19.9 months (95% confidence interval [95% CI, 13.9 months-31.1months]); group B (those with 2-4 risk factors), 5.0 months (95% CI, 4.3 months -5.6 months); and group C (those with 5-6 risk factors), 1.7 months (95% CI, 1.2 months-2.1 months). CONCLUSIONS The TEACHH model (type of cancer, Eastern Cooperative Oncology Group performance status, age, prior palliative chemotherapy, prior hospitalizations, and hepatic metastases) divides patients receiving palliative RT into 3 distinct LE groups at clinically informative extremes of the LE spectrum. It holds promise to assist radiation oncologists in tailoring palliative therapies to a patient's LE. Cancer 2014;120:134-141. © 2013 American Cancer Society. [ABSTRACT FROM AUTHOR]

Novel treatments for multiple myeloma ( MM) have shown promising results in clinical trials, but the advantage in unselected patients is still unclear. In order to evaluate whether novel therapies impact survival of MM patients, we performed a population-based analysis on data collected by the Modena Cancer Registry from 1989 to 2009. The analysis evaluated 1206 newly diagnosed MM patients collected in the years 1988-96 (conventional therapy), 1997-05 (high dose melphalan and autologous transplant), and 2006-09 (novel agents era). Both relative survival ( RS) and overall survival ( OS) improved over the years, but not equally in the three groups. For patients aged <65 years, RS improved in 1997-05 and 2006-09 compared with previous years and a trend to improvement was observed from 1997-05 to 2006-09. For patients aged 65-74 years, RS improved significantly in 2006-09 compared with 1988-96 and 1997-05. No amelioration was observed for patients 75+ years old. OS confirmed RS. In conclusion, the survival of MM patients aged <65 and, in particular, 65-74 years, has improved over time, especially after 2006. This observation provides circumstantial evidence that novel therapies might impact patient survival. Despite the limits of this study, these data refer to an unselected population, giving a picture of every day clinical practice. [ABSTRACT FROM AUTHOR]

This report represents a further update of the consensus panel criteria for the assessment of clinical response in patients with Waldenström macroglobulinaemia ( WM). These criteria have been updated in light of further data demonstrating an improvement in categorical responses with new drug regimens as well as acknowledgement of the fact that such responses are predictive of overall outcome. A number of key changes are proposed but challenges do however remain and these include the variability in kinetics of immunoglobulin M ( IgM) reduction with different treatment modalities and the apparent discrepancy between IgM and bone marrow/tissue response noted with some regimens. Planned sequential bone marrow assessments are encouraged in clinical trials. [ABSTRACT FROM AUTHOR]

Zonisamide is a benzisoxazole derivative, chemically unrelated to other antiepileptic drugs, that appears to have multiple mechanisms of action, including inhibition of Na+ channels and reduction of T-type Ca2+ currents. It is currently licensed in Europe and the USA for adjunctive treatment of partial seizures in adults, and in Europe as monotherapy for treatment of partial seizures in adults with newly diagnosed epilepsy. Zonisamide displays predictable, dose-dependent pharmacokinetics and has a half-life of ~60 h, allowing once- or twice-daily administration. It has a low potential for interactions with other medications, including oral contraceptives. The clinical efficacy of adjunctive zonisamide therapy has been established in four pivotal, phase III, randomized, double-blind, placebo-controlled trials, which together included approximately 850 patients, aged 12-77 years, with refractory partial epilepsy. In all four trials, zonisamide 300-600 mg/day resulted in significant reductions in median total seizure rates vs placebo, and zonisamide was generally well tolerated; the most frequently reported adverse events being somnolence, dizziness and anorexia/weight loss. Subanalysis of the primary European trial indicated that zonisamide was effective when administered as first-line adjunctive treatment, and a long-term extension to the same trial demonstrated that the efficacy and safety/tolerability of adjunctive zonisamide was sustained for up to 36 months. Once-daily monotherapy with zonisamide (200-500 mg/day) has been shown to be non-inferior to, and as well tolerated as, twice-daily monotherapy with controlled-release carbamazepine (400-1200 mg/day) in adults with newly diagnosed partial epilepsy. Zonisamide has also been shown to have favourable long-term retention rates, an important indication of its overall effectiveness. [ABSTRACT FROM AUTHOR]

Heart failure is still a large medical problem, and the European Journal of Heart Failure remains dedicated to further investigating its pathophysiology and diagnosis, as well as alleviating the symptoms and improving outcome for patients with this disorder.1 In 2010, a large number of important studies have been published, many with exciting results. In this overview, we discuss the results of many of these studies, which have been conducted in a broad range of areas, ranging from pre-clinical research, to co-morbidities, new insights in the genetics of heart failure, and novel guidelines in the field of device therapy. [ABSTRACT FROM PUBLISHER]

Aims Randomized clinical trials have suggested that treatment of anaemia with erythropoiesis-stimulating agents (ESAs) in patients with cancer or chronic kidney disease may increase cardiovascular risk. We therefore examined the effect of treating anaemia with an ESA in patients with heart failure in a meta-analysis of randomized clinical trials, including the recently reported TREAT study. Methods and results We performed a systematic review and meta-analysis of all prospective, randomized, controlled studies of ESAs enrolling patients with heart failure and reporting data on mortality or non-fatal heart failure events. Of 10 trials initially identified by our search strategy, we pooled data from 9 placebo-controlled studies enrolling a total of 2039 patients, of whom 1023 (50.2%) were allocated to ESA treatment. The pooled risk ratio for ESA treatment relative to placebo was 1.03 [95% confidence interval (CI): 0.89-1.21, P = 0.68] for overall mortality and 0.95 (95% CI: 0.82-1.10, P = 0.46) for worsening heart failure. Conclusions The use of ESAs to manage anaemia in patients with heart failure was associated with a neutral effect on both mortality and non-fatal heart failure events. Definitive assessment of the balance of risk and benefit in this population awaits the completion of a randomized clinical trial adequately powered to assess clinical outcomes. [ABSTRACT FROM AUTHOR]