Sample size estimation for recurrent event data using multifrailty and multilevel survival models.

In epidemiology and clinical research, recurrent events refer to individuals who are likely to experience transient clinical events repeatedly over an observation period. Examples include hospitalizations in patients with heart failure, fractures in osteoporosis studies and the occurrence of new lesions in oncology. We provided an in-depth analysis of the sample size required for the analysis of recurrent time-to-event data using multifrailty or multilevel survival models. We covered the topic from the simple shared frailty model to models with hierarchical or joint frailties. We relied on a Wald-type test statistic to estimate the sample size assuming either a single or multiple endpoints. Simulations revealed that the sample size increased as heterogeneity increased. We also observed that it was more attractive to include more patients and reduce the duration of follow-up than to include fewer patients and increase the duration of follow-up to obtain the number of events required. Each model investigated can address the question of the number of subjects for recurrent events. However, depending on the research question, one model will be more suitable than another. We illustrated our methodology with the AFFIRM-AHF trial investigating the effect of intravenous ferric carboxymaltose in patients hospitalised for acute heart failure.

Evolution of Patterns of Care and Outcomes in the Real-Life Setting for Patients with Metastatic GIST Treated in Three French Expert Centers over Three Decades.

Gastrointestinal stromal tumors (GIST) are rare mesenchymal tumors characterized by KIT or PDGFRA mutations. Over three decades, significant changes in drug discovery and loco-regional (LR) procedures have impacted treatment strategies. We assessed the evolution of treatment strategies for metastatic GIST patients treated in the three national coordinating centers of NetSarc, the French network of sarcoma referral centers endorsed by the National Institute of Cancers, from 1990 to 2018. The primary objective was to describe the clinical and biological profiles as well as the treatment modalities of patients with metastatic GIST in a real-life setting, including access to clinical trials and LR procedures in the metastatic setting. Secondary objectives were to assess (1) patients' outcome in terms of time to next treatment (TNT) for each line of systemic treatment, (2) patients' overall survival (OS), (3) evolution of patients' treatment modalities and OS according to treatment access: <2002 (pre-imatinib approval), 2002-2006 (pre-sunitinib approval), 2006-2014 (pre-regorafenib approval), post 2014, and (4) the impact of clinical trials and LR procedures on TNT and OS in the metastatic setting. 1038 patients with a diagnosis of GIST made in one of the three participating centers between 1990 and 2018 were included in the national prospective database. Among them, 492 patients presented metastasis, either synchronous or metachronous. The median number of therapy lines in the metastatic setting was 3 (range 0-15). More than half of the patients (55%) participated in a clinical trial during the course of their metastatic disease and half (51%) underwent additional LR procedures on metastatic sites. The median OS in the metastatic setting was 83.4 months (95%CI [72.7; 97.9]). The median TNT was 26.7 months (95%CI [23.4; 32.3]) in first-line, 10.2 months (95%CI [8.6; 11.8]) in second line, 6.7 months (95%CI [5.3; 8.5]) in third line, and 5.5 months (95%CI [4.3; 6.7]) in fourth line, respectively. There was no statistical difference in OS in the metastatic setting between the four therapeutic periods (log rank, p = 0.18). In multivariate analysis, age, AFIP Miettinen classification, mutational status, surgery of the primary tumor, participation in a clinical trial in the first line and LR procedure to metastatic sites were associated with longer TNT in the first line, whereas age, mitotic index, mutational status, surgery of the primary tumor and LR procedure to metastatic sites were associated with longer OS. This real-life study advocates for early reference of metastatic GIST patients to expert centers to orchestrate the best access to future innovative clinical trials together with LR strategies and further improve GIST patients' survival.

Chemotherapy following immune checkpoint inhibitors in patients with locally advanced or metastatic urothelial carcinoma.

BACKGROUND: Recent studies suggest improvements in response to salvage chemotherapy (CT) after immune checkpoint inhibitors (ICIs) in several types of cancer. Our objective was to assess the efficacy of chemotherapy re-challenge after ICI, compared with second-line chemotherapy without previous ICI in patients with locally advanced or metastatic urothelial carcinoma (la/mUC). METHODS: In this multicentre retrospective study, we included all patients with la/mUC initiating second or third-line chemotherapy from January 2015 to June 2020. We compared patients treated with second-line chemotherapy without previous ICI (CT2) and patients treated with third-line chemotherapy after ICI (CT3). The primary end-point was objective response rate (ORR) in CT3 compared with CT2. Secondary end-points included progression-free survival (PFS) and toxicities. RESULTS: Overall, 553 patients were included. ORRs were 31.0% (95% CI, 26.5 to 35.5) and 29.2% (95% CI, 21.9 to 36.6), respectively, in CT2 and CT3, with no statistically significant differences (P = 0.62). In subgroup analyses, no differences in ORR were observed by Bellmunt risk group, type of chemotherapy (platinum or taxanes), duration of response to first-platinum-based chemotherapy (< or ≥ 12 months) or FGFR-status. Median PFS was 4.6 months (95% CI, 3.9 to 5.1) and 4.9 months (95% CI, 4.1 to 5.5) in CT2 and CT3, respectively, and grade 3-4 hematologic toxicity occurred in 35.0% and 22.4% of patients. CONCLUSION: This large multicentre retrospective study provides clinically relevant real-world data. Chemotherapy re-challenge after ICI in la/mUC achieves ORR and PFS comparable with those obtained in CT2 with an acceptable safety profile. These updated results offer more promising outcomes than historically reported with second-line chemotherapy data.

Sample size estimation for cancer randomized trials in the presence of heterogeneous populations.

A key issue when designing clinical trials is the estimation of the number of subjects required. Assuming for multicenter trials or biomarker-stratified designs that the effect size between treatment arms is the same among the whole study population might be inappropriate. Limited work is available for properly determining the sample size for such trials. However, we need to account for both, the heterogeneity of the baseline hazards over clusters or strata but also the heterogeneity of the treatment effects, otherwise sample size estimates might be biased. Most existing methods account for either heterogeneous baseline hazards or treatment effects but they dot not allow to simultaneously account for both sources of variations. This article proposes an approach to calculate sample size formula for clustered or stratified survival data relying on frailty models. Both theoretical derivations and simulation results show the proposed approach can guarantee the desired power in worst case scenarios and is often much more efficient than existing approaches. Application to a real clinical trial designs is also illustrated.

Molecular profiling of advanced soft-tissue sarcomas: the MULTISARC randomized trial.

BACKGROUND: Soft-tissue sarcomas (STS) represent a heterogeneous group of rare tumors including more than 70 different histological subtypes. High throughput molecular analysis (next generation sequencing exome [NGS]) is a unique opportunity to identify driver mutations that can change the usual one-size-fits-all treatment paradigm to a patient-driven therapeutic strategy. The primary objective of the MULTISARC trial is to assess whether NGS can be conducted for a large proportion of metastatic STS participants within a reasonable time, and, secondarily to determine whether a NGS-guided therapeutic strategy improves participant's outcome. METHODS: This is a randomized, multicentre, phase II/III trial inspired by the design of umbrella and biomarker-driven trials. The setting plans up to 17 investigational centres across France and the recruitment of 960 participants. Participants aged at least 18 years, with unresectable locally advanced and/or metastatic STS confirmed by the French sarcoma pathological reference network, are randomized according to 1:1 allocation ratio between the experimental arm "NGS" and the standard "No NGS". NGS will be considered feasible if (i) NGS results are available and interpretable, and (ii) a report of exome sequencing including a clinical recommendation from a multidisciplinary tumor board is provided to investigators within 7 weeks from reception of the samples on the biopathological platform. A feasibility rate of more than 70% is expected (null hypothesis: 70% versus alternative hypothesis: 80%). In terms of care, participants randomized in "No NGS" arm and who fail treatment will be able to switch to the NGS arm at the request of the investigator. DISCUSSION: The MULTISARC trial is a prospective study designed to provide high-level evidence to support the implementation of NGS in routine clinical practice for advanced STS participants, on a large scale. TRIAL REGISTRATION: clinicaltrial.gov NCT03784014 .

Feasibility of high-throughput sequencing in clinical routine cancer care: lessons from the cancer pilot project of the France Genomic Medicine 2025 plan.

BACKGROUND: Whole exome sequencing and RNA sequencing (WES/RNASeq) should now be implemented in the clinical practice in order to increase access to optimal care for cancer patients. Providing results to Tumour Boards in a relevant time frame-that is, compatible with the clinical pathway-is crucial. Assessing the feasibility of this implementation in the French care system is the primary objective of the Multipli study, as one of the four pilot projects of the national France Genomic Medicine 2025 (FGM 2025) plan. The Multipli study encompasses two innovative trials which will be driven in around 2400 patients suffering from a soft-tissue sarcoma (Multisarc) or a metastatic colorectal carcinoma (Acompli). METHODS: Prior to launching the FGM 2025 cancer pilot study itself, the performance of the Multipli genomic workflow has been evaluated through each step, from the samples collection to the Molecular Tumour Board (MTB) report. Two Multipli-assigned INCa-labelled molecular genetics centres, the CEA-CNRGH sequencing platform and the Institut Bergonié's Bioinformatics Platform were involved in a multicentric study. The duration of each step of the genomic workflow was monitored and bottlenecks were identified. RESULTS: Thirty barriers which could affect the quality of the samples, sequencing results and the duration of each step of the genomic pathway were identified and mastered. The global turnaround time from the sample reception to the MTB report was of 44 calendar days. CONCLUSION: Our results demonstrate the feasibility of tumour genomic analysis by WES/RNASeq within a time frame compatible with the current cancer patient care. Lessons learnt from the Multipli WES/RNASeq Platforms Workflow Study will constitute guidelines for the forthcoming Multipli study and more broadly for the future clinical routine practice in the first two France Genomic Medicine 2025 platforms.

Outcome of Patients with Soft-Tissue Sarcomas: An Age-Specific Conditional Survival Analysis.

BACKGROUND: Soft-tissue sarcomas (STSs) are a group of rare cancers that can occur at any age. Prognostic outcomes of patients with STS are usually established at the time of the patient's initial disease presentation. Conditional survival affords a dynamic prediction of prognosis for patients surviving a given period after diagnosis. Estimates of conditional survival can provide crucial prognostic information for patients and caregivers, guide subsequent cancer follow-up schedules, and impact decisions regarding management. This study aims to estimate conditional survival and prognostic factors in patients with STS according to age at diagnosis (≤75 years and ≥75 years). SUBJECTS, MATERIALS, AND METHODS: A total of 6,043 patients with nonmetastatic STS at first diagnosis who underwent complete surgical resection (R0 or R1) were assessed. Cox proportional hazards regression was used to establish prognostic factors of conditional metastasis-free survival and overall survival at 1, 2, and 5 years after diagnosis. RESULTS: Elderly patients have more adverse prognostic features at presentation and tend to receive less aggressive treatment than do younger patients. However, at baseline as well as at each conditional survival time point, the 5-year estimated probability of metastatic relapse decreases in both young and elderly patients and is almost identical in both groups at 2 years and 5 years after initial diagnosis. Prognostic factors for metastatic relapse and death change as patient survival time increases in both young and elderly patients. Grade, the strongest prognostic factor for metastatic relapse and death at baseline, is no longer predictive of metastatic relapse in patients surviving 5 years after initial diagnosis. Leiomyosarcoma is the histological subtype associated with the highest risk of metastatic relapse and death in young patients surviving 5 years after initial diagnosis. The positive impact on the outcome of peri-operative treatments tends to decrease and disappears in patients surviving 5 years after initial diagnosis. CONCLUSION: Conditional survival estimates show clinically relevant variations according to time since first diagnosis in both young and elderly patients with STS. These results can help STS survivors adjust their view of the future and STS care providers plan patient follow-up. IMPLICATIONS FOR PRACTICE: For patients with sarcoma who are followed up years after being treated for their disease, a common scenario is for the patient and caregivers to ask practitioners what the longer-term prognosis may be. The question posed to practitioners may be, "Doc, am I now cured? It's been 5 years since we finished treatment." Survival probability changes for patients who survive a given period of time after diagnosis, and their prognosis is more accurately described using conditional survival. By analyzing more than 6,000 sarcoma patients, an overall improvement was found in the risk of relapse as patients conditionally survive. Prognostic factors for metastatic relapse and death change as patient survival time increases in both young and elderly patients.

Meta-analyses evaluating surrogate endpoints for overall survival in cancer randomized trials: A critical review.

BACKGROUND: In cancer randomized controlled trials (RCT), alternative endpoints are increasingly being used in place of overall survival (OS) to reduce sample size, duration and cost of trials. It is necessary to ensure that these endpoints are valid surrogates for OS. Our aim was to identify meta-analyses that evaluated surrogate endpoints for OS and assess the strength of evidence for each meta-analysis (MA). MATERIALS AND METHODS: We performed a systematic review to identify MA of cancer RCTs assessing surrogate endpoints for OS. We evaluated the strength of the association between the endpoints based on (i) the German Institute of Quality and Efficiency in Health Care guidelines and (ii) the Biomarker-Surrogate Evaluation Schema. RESULTS: Fifty-three publications reported on 164 MA, with heterogeneous statistical methods Disease-free survival (DFS) and progression-free survival (PFS) showed good surrogacy properties for OS in colorectal, lung and head and neck cancers. DFS was highly correlated to OS in gastric cancer. CONCLUSION(S): The statistical methodology used to evaluate surrogate endpoints requires consistency in order to facilitate the accurate interpretation of the results. Despite the limited number of clinical settings with validated surrogate endpoints for OS, there is evidence of good surrogacy for DFS and PFS in tumor types that account for a large proportion of cancer cases.