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Increased risk of urinary tract infection and pyelonephritis under concomitant use of sodium-dependent glucose cotransporter 2 inhibitors with antidiabetic, antidyslipidemic, and antihypertensive drugs: An observational study

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FUNDAMENTAL & CLINICAL PHARMACOLOGY 2022年第6期36卷 1106-1114页

作者： Tada, Keisuke Gosho, Masahiko Sanofi KK Biostat & Programming Tokyo Opera City Tower Tokyo Japan Univ Tsukuba Grad Sch Comprehens Human Sci Ibaraki Japan Univ Tsukuba Fac Med Dept Biostat Ibaraki Japan

Urinary tract infection (UTI) and pyelonephritis cause urosepsis, which can become life threating. Sodium-dependent glucose cotransporter 2 (SGLT2) inhibitors, a class of oral anti-diabetic drugs, may increase the risk of UTI and pyelonephritis, as observed from their mechanism of action. Patients with diabetes receiving SGLT2 inhibitors are often concomitantly administered other antidiabetic, antidyslipidemic, or antihypertensive drugs. To determine if drug-drug interactions (DDIs) between SGLT2 inhibitors and these medications increased the risk of UTI and pyelonephritis, we analyzed the Food and Drug Administration Adverse Event Reporting System (FAERS) database. We applied Noren's and Gosho's methods for detecting DDIs. FAERS contains records describing 14 526 398 patient characteristics, 54 290 663 drug properties, and 47 252 416 reactions/events. We found 23 drug combinations that could induce UTI and pyelonephritis, such as SGLT2 inhibitors administered with dipeptidyl peptidase-4 inhibitors, thiazolidinediones, glinides, statins, angiotensin II receptor blockers, and calcium channel blockers. Combination therapy with the drugs detected in our analyses would show potential interactions that could result in UTI and pyelonephritis in patients with diabetes mellitus. However, owing to various limitations, these results must be confirmed by additional analyses.

关键词： Bayesian confidence propagation neural network method drug-drug interaction reporting odds ratio signal detection spontaneous reporting system

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A Flexible Ensemble Learning Method for Survival Extrapolation

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THERAPEUTIC INNOVATION & REGULATORY SCIENCE 2023年第3期57卷 580-588页

作者： Dai, Ran Ma, Jihyun Wu, Meijing Mai, Yabing He, Weili Univ Nebraska Med Ctr Dept Biostat Omaha NE USA Sanofi US Serv Inc Biostat & Stat Programming 450 Water St Cambridge MA 02141 USA Boehringer Ingelheim GmbH & Co KG Biostat & Data Sci TCM Shanghai Peoples R China Abbvie Inc Data & Stat Sci N Chicago IL USA

Objectives Survival extrapolation is an important statistical concept for estimating long-term survival from short-term clinical trial data. It is widely used in health technology assessment (HTA). Survival extrapolation is often performed by fitting one or two parametric models selected based on experience or selecting a model based on some goodness of fit statistics from a predefined collection of models. The main challenge in survival extrapolation is that the result is sensitive to model misspecification. In this study, we aim to propose a new approach that has a robust performance for survival extrapolation. Methods We propose a new method called Ensemble Learning for Survival Extrapolation (ELSE). Instead of selecting one best model from a predefined collection, ELSE builds an ensemble model based on a collection of models from the model library. Under this framework, we construct a point estimate of the long-term survival with a weighted average of the estimates of all candidate models and derive confidence intervals using nonparametric bootstrap. Results With our extensive numerical simulation studies, the proposed ELSE method shows better performance than the traditionally used model selection procedure based on Akaike Information Criterion (AIC). With a real data application to the Therapeutically Applicable Research to Generate Effective Treatment Wilms Tumor project (TARGET-WT) data, the ELSE method produces better survival extrapolation results in point estimate accuracy and confidence interval coverage. Conclusions We developed an ensemble learning method for survival extrapolation (ELSE) which is robust for the underline data model and has good real data performance.

关键词： Survival analysis Ensemble learning Survival extrapolation Bootstrap Health technology assessment

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Evaluating Treatment Efficacy by Combining Multiple Measures in Clinical Trial Applications

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PHARMACEUTICAL MEDICINE 2023年第1期37卷 7-16页

作者： Al Masud, Abdullah Weerahandi, Samaradasa Yu, Ching-Ray Sanofi US Biostat & Programming 55 Corp Dr Bridgewater NJ 08807 USA X Tech LLC Edison NJ USA Pfizer Inc New York NY USA

A variety of clinical and laboratory measures can be used in clinical trials to assess the benefit of a new treatment over the standard of care. Data from clinical studies are often analyzed by combining individual outcomes into one primary outcome. That primary outcome is then referred to as a composite endpoint or a combined endpoint. We propose an analysis on the composite endpoint with Gehan's (1965) ranking approach where each subject in the treatment group is compared with each subject in the control group in a pair-wise manner. Our approach reduces computational time and complexity to construct a subject-level pairwise composite score. We develop a statistical testing procedure for the analysis of composite endpoints when using the hierarchical scores. In this article, we propose two tests (a parametric test and a non-parametric bootstrap procedure) for evaluating the effect of treatment. The proposed parametric test has an asymptotic F-distribution based on standard statistical assumptions. We conduct an extensive simulation study to assess the operating characteristics of the proposed methods and to compare them with an existing method. We illustrate the methods using publicly available data from two clinical studies.

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Phase I study of aflibercept in combination with docetaxel in Japanese patients with advanced solid malignancies

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INVESTIGATIONAL NEW DRUGS 2022年第5期40卷 1032-1041页

作者： Sunakawa, Yu Takahashi, Keishiro Kawaguchi, Osamu Yamamoto, Nobuyuki St Marianna Univ Dept Clin Oncol Sch Med Kawasaki Kanagawa Japan Sanofi Res & Dev Tokyo Japan Sanofi Biostat & Programming Tokyo Japan Wakayama Med Univ Hosp Dept Internal Med 3 Wakayama Japan

Angiogenesis is a hallmark of cancer development. This study sought to determine the recommended dose of aflibercept, a recombinant fusion protein targeting VEGF-A, VEGF-B and placental growth factor (PlGF), combined with docetaxel in Japanese patients with advanced solid malignancies. This phase I study was planned to include 12 patients following a 3 + 3 algorithm to determine the maximum tolerated dose of aflibercept combined with docetaxel in patients with metastatic or unresectable solid tumors (trial registration: NCT00545246). Docetaxel (75 mg/m(2) every 3 weeks or 60 mg/m(2) after protocol amendment) was combined with escalating doses of aflibercept (2, 4 and 6 mg/kg every 4 weeks). Free and VEGF-bound aflibercept were measured to assess free aflibercept in excess of the VEGF-bound form. At the starting dose of the combination, 3 of 6 patients treated experienced febrile neutropenia. After reducing the docetaxel dose to 60 mg/m(2) in step 2 and permitting therapeutic granulocyte colony-stimulating factor (G-CSF) use, 2 of 3 patients in both cohorts experienced febrile neutropenia. Five patients (42%) had a partial response and 4 patients had stable disease (33%). Free aflibercept in excess of the VEGF-bound form was not maintained at this dose level. The dose limiting toxicity (DLT) of aflibercept combined with docetaxel was febrile neutropenia, which occurred in 2 of 3 Japanese patients at the lowest aflibercept dose level (2 mg/kg) combined with docetaxel (60 mg/m(2)) and therapeutic G-CSF use. A recommended dose for further studies was not determined because of the DLT at the starting dose.

关键词： Aflibercept Docetaxel Dose escalation Japanese VEGF Trap

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Efficacy and safety of dupilumab with concomitant topical corticosteroids in Japanese pediatric patients with moderate-to-severe atopic dermatitis: A randomized, double-blind, placebo-controlled phase 3 study

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ALLERGOLOGY INTERNATIONAL 2024年第4期73卷 532-542页

作者： Ebisawa, Motohiro Kataoka, Yoko Tanaka, Akio Nagao, Mizuho Laws, Elizabeth Mortensen, Eric Nawata, Hisakatsu Arima, Kazuhiko Watanabe, Daisuke Lu, Xin Maloney, Jennifer Dubost-Brama, Ariane Bansal, Ashish Yahata, Kenji NHO Sagamihara Natl Hosp Clin Res Ctr Allergy & Rheumatol Sagamihara Japan Osaka Habikino Med Ctr Dept Dermatol Osaka Japan Hiroshima Univ Grad Sch Biomed Sci Dept Dermatol Hiroshima Japan NHO Mie Natl Hosp Allergy Ctr Tsu Japan NHO Mie Natl Hosp Infect Dis Ctr Tsu Japan Sanofi Bridgewater NJ USA Regeneron Pharmaceut Tarrytown NY USA Sanofi KK Immunol Med Tokyo Japan Sanofi KK Biostat & Programming Tokyo Japan Sanofi R&D Chilly Mazarin France Sanofi KK Res & Dev Div Tokyo Japan

Background We investigated the efficacy and safety of dupilumab in Japanese patients aged >= 6 months to = 75% improvement in Eczema Area and Severity Index (EASI) score from baseline (EASI-75) to Week 16. Key seco... 详细信息

Background We investigated the efficacy and safety of dupilumab in Japanese patients aged >= 6 months to <18 years old with moderate-to-severe atopic dermatitis not adequately controlled with existing therapies. Methods In this randomized, double-blind, phase 3 study, patients received dupilumab (n = 30) or placebo (n = 32) with concomitant topical corticosteroids for 16 weeks, then all patients received dupilumab from 16 to 52 weeks. The primary endpoint was the proportion of patients with >= 75% improvement in Eczema Area and Severity Index (EASI) score from baseline (EASI-75) to Week 16. Key secondary endpoints included changes in EASI score, proportion of patients with investigator global assessment (IGA) scores of 0/1, and changes in worst daily itch numerical rating scale (NRS) scores (evaluated in patients aged >= 6 to <12 years [n = 35]). Results At Week 16, more patients achieved EASI-75 with dupilumab than placebo (43.3% vs 18.8%;P = 0.0304), and the least squares mean (LSM) difference in percent change in EASI scores at Week 16 of dupilumab vs placebo was -39.4% (P = 0.0003). However, no significant difference in the proportion of patients achieving IGA scores of 0/1 at Week 16 with dupilumab versus placebo were seen (10.0% vs 9.4%;P = 0.8476). The percent change in worst daily itch NRS scores at Week 16 was higher with dupilumab (LSM difference: -33.3%;nominal P = 0.0117). Dupilumab was well tolerated;no new safety signals were identified. Conclusions Dupilumab showed consistent efficacy and was well tolerated in Japanese patients aged >= 6 months to <18 years with moderate-to-severe atopic dermatitis previously insufficiently controlled with existing therapies.(c) 2024 Japanese Society of Allergology. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Atopic Dermatitis Dupilumab Japanese Pediatrics

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A simulation-free group sequential design with max-combo tests in the presence of non-proportional hazards

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PHARMACEUTICAL STATISTICS 2021年第4期20卷 879-897页

作者： Wang, Lili Luo, Xiaodong Zheng, Cheng Univ Michigan Dept Biostat Ann Arbor MI 48109 USA Sanofi US Dept Biostat & Programming Res & Dev Bridgewater NJ 08807 USA

Non-proportional hazards (NPH) have been observed in many immuno-oncology clinical trials. Weighted log-rank tests (WLRT) with suitable weights can be used to improve the power of detecting the difference between survival curves in the presence of NPH. However, it is not easy to choose a proper WLRT in practice. A versatile max-combo test was proposed to achieve the balance of robustness and efficiency, and has received increasing attention recently. Survival trials often warrant interim analyses due to their high cost and long durations. The integration and implementation of max-combo tests in interim analyses often require extensive simulation studies. In this report, we propose a simulation-free approach for group sequential designs with the max-combo test in survival trials. The simulation results support that the proposed method can successfully control the type I error rate and offer excellent accuracy and flexibility in estimating sample sizes, with light computation burden. Notably, our method displays strong robustness towards various model misspecifications and has been implemented in an R package.

关键词： group sequential design interim analysis max‐ combo non‐ proportional hazard weighted log‐ rank test

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Teasing Out the Overall Survival Benefit With Adjustment for Treatment Switching to Multiple Treatments

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STATISTICS IN BIOPHARMACEUTICAL RESEARCH 2022年第4期14卷 592-601页

作者： Xu, Yuqing Wu, Meijing He, Weili Liao, Qiming Mai, Yabing Sanofi US Biostat & Programming Bridgewater NJ USA AbbVie Inc Data & Stat Sci N Chicago IL 60064 USA ViiV Healthcare Dept Stat Raleigh NC USA Boehringer Ingelheim GmbH & Co KG Biostat Asia Shanghai Peoples R China

In oncology clinical trials, characterizing the long-term overall survival (OS) benefit for an experimental treatment is often unobservable if some patients in the control group switch to drugs in the experimental group and/or other cancer treatments after disease progression. A key question often raised by payers and reimbursement agencies is how to estimate the true benefit of the experimental treatment on OS that would have been estimated if there were no treatment switches. Several commonly used statistical methods are available to estimate OS benefit while adjusting for treatment switching, ranging from naive exclusion or censoring approaches to more advanced methods including inverse probability of censoring weighting (IPCW), two-stage model (2-stage), iterative parameter estimation (IPE) algorithm or rank-preserving structural failure time models (RPSFTM). However, many clinical trials now have patients in the control group switching to different treatment regimens other than the experimental treatments. While some existing methods including RPSFTM and IPE cannot handle complicated scenarios such as multilevel switching, other methods such as IPCW and two-stage methods are restricted with strong assumptions. To address this challenge, we propose two additional methods: stratified RPSFTM and random-forest-based prediction. A simulation study is conducted to assess the performance of the existing methods along with the two newly proposed approaches.

关键词： Oncology Overall survival Randomized trials Rank-preserving structural failure time models Treatment switching

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Immunogenicity and safety of an investigational quadrivalent meningococcal conjugate vaccine administered as a booster dose in children vaccinated against meningococcal disease 3 years earlier as toddlers: A Phase III, open-label, multi-center study

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HUMAN VACCINES & IMMUNOTHERAPEUTICS 2022年第1期18卷 1-10页

作者： Piazza, Franco M. Virta, Miia Paassilta, Marita Ukkonen, Benita Ahonen, Anitta Esteves-Jaramillo, Alejandra Forsten, Aino Seppa, Ilkka Ding, Jian Neveu, David Jordanov, Emilia Dhingra, Mandeep S. Sanofi Pasteur Global Clin Dev 1 Discovery Dr Swiftwater PA 18370 USA Tampere Univ Vaccine Res Ctr Tampere Finland Tampere Univ Espoo Vaccine Res Clin Tampere Finland Sanofi Clin Sci Operat Biostat & Programming Beijing Peoples R China Sanofi Pasteur Global Pharmacovigilance Swiftwater PA USA

Booster doses of meningococcal conjugate vaccines induce long-term protection against invasive meningococcal disease. We evaluated the immunogenicity and safety of a booster dose of MenACYW-TT in pre-school children who were primed 3 years earlier with MenACYW-TT or MCV4-TT (Nimenrix (R)). In this Phase III, open-label, multi-center study (NCT03476135), children (4-5 years old), who received a primary dose of MenACYW-TT or MCV4-TT as toddlers in a previous study, received a booster dose of MenACYW-TT. Titers of antibody against meningococcal serogroups A, C, W and Y were measured by serum bactericidal assay using human (hSBA) and baby rabbit (rSBA) complement in samples collected before (D0) and 30 days after (D30) booster vaccination. Safety was assessed over the 30-day study period. Ninety-one participants received the booster dose. In both study groups, hSBA titers increased from D0 to D30;serogroup C titers [95% confidence interval] were higher in the MenACYW-TT-primed vs MCV4-TT-primed group at D0 (106 [73.2, 153] vs 11.7 [7.03, 19.4], respectively) and D30 (5894 [4325, 8031] vs 1592 [1165, 2174], respectively);rSBA results were similar. Nearly all participants achieved >= 1:8 hSBA and rSBA titers at D30, which were higher or comparable to those observed post-primary dose, suggesting rapid booster responses. At D0, all hSBA and rSBA titers were higher than those observed pre-primary dose, suggesting persistence of immunogenicity. The MenACYW-TT booster dose was well-tolerated and had similar safety outcomes across study groups. These findings suggest that MenACYW-TT elicits robust booster responses in children primed 3 years earlier with MenACYW-TT or MCV4-TT.

关键词： Meningococcal pre-school children MenACYW-TT quadrivalent meningococcal conjugate vaccine booster

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Implementation of tripartite estimands using adherence causal estimators under the causal inference framework

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PHARMACEUTICAL STATISTICS 2021年第1期20卷 55-67页

作者： Qu, Yongming Luo, Junxiang Ruberg, Stephen J. Eli Lilly & Co Dept Biometr Indianapolis IN 46285 USA Sanofi Biostat & Programming Bridgewater NJ USA Analytix Thinking LCC Indianapolis IN USA

Intercurrent events (ICEs) and missing values are inevitable in clinical trials of any size and duration, making it difficult to assess the treatment effect for all patients in randomized clinical trials. Defining the appropriate estimand that is relevant to the clinical research question is the first step in analyzing data. The tripartite estimands, which evaluate the treatment differences in the proportion of patients with ICEs due to adverse events, the proportion of patients with ICEs due to lack of efficacy, and the primary efficacy outcome for those who can adhere to study treatment under the causal inference framework, are of interest to many stakeholders in understanding the totality of treatment effects. In this manuscript, we discuss the details of how to estimate tripartite estimands based on a causal inference framework and how to interpret tripartite estimates through a phase 3 clinical study evaluating a basal insulin treatment for patients with type 1 diabetes.

关键词： adherence ICH E9 (R1) intercurrent events missing data principal stratification

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Bayesian methods for the analysis of early-phase oncology basket trials with information borrowing across cancer types

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STATISTICS IN MEDICINE 2020年第25期39卷 3459-3475页

作者： Jin, Jin Riviere, Marie-Karelle Luo, Xiaodong Dong, Yingwen Johns Hopkins Univ Bloomberg Sch Publ Hlth Dept Biostat 615 N Wolfe St Baltimore MD 21205 USA Sanofi Res & Dev Dept Biostat & Programming Chilly Mazarin France Sanofi Dept Biostat & Programming Bridgewater MA USA Sanofi Dept Biostat & Programming Oncol Cambridge MA USA

Research in oncology has changed the focus from histological properties of tumors in a specific organ to a specific genomic aberration potentially shared by multiple cancer types. This motivates the basket trial, which assesses the efficacy of treatment simultaneously on multiple cancer types that have a common aberration. Although the assumption of homogeneous treatment effects seems reasonable given the shared aberration, in reality, the treatment effect may vary by cancer type, and potentially only a subgroup of the cancer types respond to the treatment. Various approaches have been proposed to increase the trial power by borrowing information across cancer types, which, however, tend to inflate the type I error rate. In this article, we review some representative Bayesian information borrowing methods for the analysis of early-phase basket trials. We then propose a novel method called the Bayesian hierarchical model with a correlated prior (CBHM), which conducts more flexible borrowing across cancer types according to sample similarity. We did simulation studies to compare CBHM with independent analysis and three information borrowing approaches: the conventional Bayesian hierarchical model, the EXNEX approach, and Liu's two-stage approach. Simulation results show that all information borrowing approaches substantially improve the power of independent analysis if a large proportion of the cancer types truly respond to the treatment. Our proposed CBHM approach shows an advantage over the existing information borrowing approaches, with a power similar to that of EXNEX or Liu's approach, but the potential to provide substantially better control of type I error rate.

关键词： basket trials Bayesian hierarchical models between-indication similarity early-phase oncology study information borrowing across cancer types

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