International Drug Development Institute
International Drug Development Institute
Paoletti X.,Institute National du Cancer |
Oba K.,Kyoto University |
Burzykowski T.,Hasselt University |
Michiels S.,Institute Gustave Roussy |
And 8 more authors.
JAMA - Journal of the American Medical Association | Year: 2010
Context: Despite potentially curative resection of stomach cancer, 50% to 90% of patients die of disease relapse. Numerous randomized clinical trials (RCTs) have compared surgery alone with adjuvant chemotherapy, but definitive evidence is lacking. Objectives: To perform an individual patient-level meta-analysis of all RCTs to quantify the potential benefit of chemotherapy after complete resection over surgery alone in terms of overall survival and disease-free survival, and to further study the role of regimens, including monochemotherapy; combined chemotherapy with fluorouracil derivatives, mitomycin C, and other therapies but no anthracyclines; combined chemotherapy with fluorouracil derivatives, mitomycin C, and anthracyclines; and other treatments. Data Sources: Data from all RCTs comparing adjuvant chemotherapy with surgery alone in patients with resectable gastric cancer. We searched MEDLINE (up to 2009), the Cochrane Central Register of Controlled Trials, the National Institutes of Health trial registry, and published proceedings from major oncologic and gastrointestinal cancer meetings. Study Selection: All RCTs closed to patient recruitment before 2004 were eligible. Trials testing radiotherapy; neoadjuvant, perioperative, or intraperitoneal chemotherapy; or immunotherapy were excluded. Thirty-one eligible trials (6390 patients) were identified. Data Extraction: As of 2010, individual patient data were available from 17 trials (3838 patients representing 60% of the targeted data) with a median follow-up exceeding 7 years. Results: There were 1000 deaths among 1924 patients assigned to chemotherapy groups and 1067 deaths among 1857 patients assigned to surgery-only groups. Adjuvant chemotherapy was associated with a statistically significant benefit in terms of overall survival (hazard ratio [HR], 0.82; 95% confidence interval [CI], 0.76-0.90; P<.001) and disease-free survival (HR, 0.82; 95% CI, 0.75-0.90; P<.001). There was no significant heterogeneity for overall survival across RCTs (P=.52) or the 4 regimen groups (P=.13). Five-year overall survival increased from 49.6% to 55.3% with chemotherapy. Conclusion: Among the RCTs included, postoperative adjuvant chemotherapy based on fluorouracil regimens was associated with reduced risk of death in gastric cancer compared with surgery alone. ©2010 American Medical Association. All rights reserved.
Hurvitz S.A.,University of California at Los Angeles |
Andre F.,University Paris - Sud |
Jiang Z.,Beijing 307 Hospital of PLA |
Shao Z.,Fudan University |
And 16 more authors.
The Lancet Oncology | Year: 2015
Background: mTOR inhibition reverses trastuzumab resistance via the hyperactivated PIK/AKT/mTOR pathway due to PTEN loss, by sensitising PTEN-deficient tumours to trastuzumab. The BOLERO-1 study assessed the efficacy and safety of adding everolimus to trastuzumab and paclitaxel as first-line treatment for patients with HER2-positive advanced breast cancer. Methods: In this phase 3, randomised, double-blind trial, patients were enrolled across 141 sites in 28 countries. Eligible patients were aged 18 years or older, with locally assessed HER2-positive advanced breast cancer, with Eastern Cooperative Oncology Group (ECOG) performance status of 0-1, who had not received previous trastuzumab or chemotherapy for advanced breast cancer within 12 months of randomisation, had measurable disease as per Response Evaluation Criteria in Solid Tumors (RECIST) or bone lesions in the absence of measurable disease, without previous systemic treatment for advanced disease except endocrine therapy. Patients were randomly assigned (2:1) with an interactive voice and web response system to receive either 10 mg everolimus once a day orally or placebo plus weekly trastuzumab intravenously at 4 mg/kg loading dose on day 1 with subsequent weekly doses of 2 mg/kg of each 4 week cycle plus paclitaxel intravenously at a dose of 80 mg/m2 on days 1, 8, and 15 of each 4 week cycle. Randomisation was stratified according to previous use of trastuzumab and visceral metastasis. Patients and investigators were masked to the assigned treatments. Identity of experimental treatments was concealed by use of everolimus and placebo that were identical in packaging, labelling, appearance, and administration schedule. The two primary objectives were investigator-assessed progression-free survival in the full study population and in the subset of patients with hormone receptor-negative breast cancer at baseline; the latter was added during the course of the study, before unmasking based on new clinical and biological findings from other studies. All efficacy analyses were based on the intention-to-treat population. Enrolment for this trial is closed and results of the final progression-free survival analyses are presented here. This trial is registered with ClinicalTrials.gov, number NCT00876395. Findings: Between Sept 10, 2009, and Dec 16, 2012, 719 patients were randomly assigned to receive everolimus (n=480) or placebo (n=239). Median follow-up was 41·3 months (IQR 35·4-46·6). In the full population, median progression-free survival was 14·95 months (95% CI 14·55-17·91) with everolimus versus 14·49 months (12·29-17·08) with placebo (hazard ratio 0·89, 95% CI 0·73-1·08; p=0·1166). In the HR-negative subpopulation (n=311), median progression-free survival with everolimus was 20·27 months (95% CI 14·95-24·08) versus 13·08 months (10·05-16·56) with placebo (hazard ratio 0·66, 95% CI 0·48-0·91; p=0·0049); however, the protocol-specified significance threshold (p=0·0044) was not crossed. The most common adverse events with everolimus were stomatitis (314 [67%] of 472 patients in the everolimus group vs 77 [32%] of 238 patients in the placebo group), diarrhoea (267 [57%] vs 111 [47%] patients), and alopecia (221 [47%] vs 125 [53%]). The most frequently reported grade 3 or 4 adverse events in the everolimus group versus the placebo group were neutropenia (117 [25%] vs 35 [15%]), stomatitis (59 [13%] vs three [1%]), anaemia (46 [10%] vs six [3%]) and diarrhoea (43 [9%] vs 10 [4%]) On-treatment adverse event-related deaths were reported in 17 (4%) patients in the everolimus group and none in the placebo group. Interpretation: Although progression-free survival was not significantly different between groups in the full analysis population, the 7·2 months prolongation we noted with the addition of everolimus in the HR-negative, HER2-positive population warrants further investigation, even if it did not meet prespecified criteria for significance. The safety profile was generally consistent with what was previously reported in BOLERO-3. Proactive monitoring and early management of adverse events in patients given everolimus and chemotherapy is crucial. Funding: Novartis Pharmaceuticals. © 2015 Elsevier Ltd.
Jackson T.L.,King's College London |
Shusterman E.M.,Oraya Therapeutics, Inc |
Arnoldussen M.,Oraya Therapeutics, Inc |
Chell E.,Oraya Therapeutics, Inc |
And 2 more authors.
Retina | Year: 2015
PURPOSE:: To determine which patients respond best to stereotactic radiotherapy (SRT) for neovascular age-related macular degeneration. METHODS:: Participants (n = 230) receiving intravitreal anti-vascular endothelial growth factor injections for neovascular age-related macular degeneration enrolled in a randomized, double-masked sham-controlled trial comparing 16 Gray, 24 Gray, or Sham SRT. In a post hoc analysis, participants were grouped according to their baseline characteristics, to determine if these influenced SRT efficacy. RESULTS:: At 52 weeks, SRT was most effective for lesions ≤4 mm in greatest linear dimension and with a macular volume greater than the median value of 7.4 mm. For 26% of the participants with both these characteristics, SRT resulted in 55% fewer ranibizumab injections (2.08 vs. 4.60; P = 0.0002), a mean visual acuity change that was 5.33 letters superior to sham (+2.18 vs. -3.15 letters; P = 0.0284), and a 71.1-μm greater reduction in mean central subfield thickness (-122.6 vs. -51.5 μm; P = 0.027). Other features associated with a positive response to SRT included pigment epithelial detachment and the absence of fibrosis. CONCLUSION:: Stereotactic radiotherapy is most effective for neovascular age-related macular degeneration lesions that are actively leaking at the time of treatment, and no larger than the 4-mm treatment zone. Copyright © by Ophthamic Communications Society.
Saad E.D.,University of Sao Paulo |
Buyse M.,International Drug Development Institute
Acta Oncologica | Year: 2012
Background. Determining the non-inferiority margin is an essential step in the design and interpretation of non-inferiority trials, and this margin should be preferably justified on clinical and statistical grounds. Methods. After a PubMed search for phase III trials in advanced breast cancer (BC) or non-small cell lung cancer (NSCLC) published between January 1998 and December 2009 in 11 leading journals, non-inferiority trials were selected by manual search of the full papers. Results. Twenty-four of 195 trials had a primary non-inferiority hypothesis. When the two six-year study periods were compared, there were time trends within BC and NSCLC, with most non-inferiority trials in BC reported in the first six-year period, and vice-versa for NSCLC. The median sample size was larger for non-inferiority than superiority trials (p <0.01). The choice of a non-inferiority margin was reportedly justified in only five cases. Non-inferiority trials were more likely than superiority trials to yield positive results (p <0.001), as were trials in breast cancer (p 0.02). Conclusions. Non-inferiority margins for cancer trials appear to be chosen mostly on historical grounds. Since nearly three-quarters of non-inferiority trials achieve their primary objective, the extent to which the choice of margins has influence on trial results remains to be determined. © 2012 Informa Healthcare.
Buyse M.,International Drug Development Institute |
Buyse M.,Hasselt University |
Michiels S.,Institute Gustave Roussy
Current Opinion in Oncology | Year: 2013
PURPOSE OF REVIEW: The derivation of signatures using-omics technologies is increasingly integrated in the design of clinical trials in oncology. In this review, we investigate the clinical trial designs for the validation of prognostic and predictive signatures. RECENT FINDINGS: Using real-life breast cancer trial examples, we highlight the pros and cons of clinical utility designs for prognostic signatures. For predictive signatures, we first review alternative procedures to test the effect of treatment in the overall population as well as in the signature-positive or signature-negative subgroup. We proceed to show why the recent literature on signature-based strategy designs discourages the use of this design. We conclude by discussing adaptive signature designs to identify and validate a signature in a single trial using cross-validation techniques. SUMMARY: Use of-omics technologies should not be an add-on to clinical trials, it must become an integral part of their design. © 2013 Wolters Kluwer Health | Lippincott Williams &Wilkins.
Buyse M.,International Drug Development Institute |
Sargent D.J.,Cancer Center Statistics |
Grothey A.,Rochester College |
Matheson A.,Fondation ARCAD |
De Gramont A.,Hopital Saint Antoine
Nature Reviews Clinical Oncology | Year: 2010
Biomarkers and surrogate end points have great potential for use in clinical oncology, but their statistical validation presents major challenges, and few biomarkers have been robustly confirmed. Provisional supportive data for prognostic biomarkers, which predict the likely outcome independently of treatment, is possible through small retrospective studies, but it has proved more difficult to achieve robust multi-site validation. Predictive biomarkers, which predict the likely response of patients to specific treatments, require more extensive data for validation, specifically large randomized clinical trials and meta-analysis. Surrogate end points are even more challenging to validate, and require data demonstrating both that the surrogate is prognostic for the true end point independently of treatment, and that the effect of treatment on the surrogate reliably predicts its effect on the true end point. In this Review, we discuss the nature of prognostic and predictive biomarkers and surrogate end points, and examine the statistical techniques and designs required for their validation. In cases where the statistical requirements for validation cannot be rigorously achieved, the biological plausibility of an end point or surrogate might support its adoption. No consensus yet exists on processes or standards for pragmatic evaluation and adoption of biomarkers and surrogate end points in the absence of robust statistical validation. © 2010 Macmillan Publishers Limited. All rights reserved.
Buyse M.,International Drug Development Institute |
Buyse M.,Hasselt University
Statistics in Medicine | Year: 2010
This paper extends the idea behind the U-statistic of the Wilcoxon-Mann-Whitney test to perform generalized pairwise comparisons between two groups of observations. The observations are outcomes captured by a single variable, possibly repeatedly measured, or by several variables of any type (e.g. discrete, continuous, time to event). When several outcomes are considered, they must be prioritized. We show that generalized pairwise comparisons extend well-known non-parametric tests, and illustrate their interest using data from two randomized clinical trials. We also show that they lead to a general measure of the difference between the groups called the 'proportion in favor of treatment', denoted Δ, which is related to traditional measures of treatment effect for a single variable. Copyright © 2010 John Wiley & Sons, Ltd.
International Drug Development Institute | Date: 2015-06-25
A method for central monitoring of a research includes the steps of creating and storing a database consisting of datasets generated during the research, preprocessing the database to remove variables that are unsuitable for analysis, extracting metadata from the database to identify types of the variables, storing the preprocessed datasets and corresponding metadata in a statistical database, executing statistical tests on a data collection center by data collection center basis to detect abnormalities and patterns present in datasets, creating and storing a matrix containing p-values based upon the executed statistical tests, identifying any outlying data collection centers by summarizing the p-values, determining if any of the executed statistical tests are faulty and removing such faulty executed statistical tests from the matrix to create a filtered matrix, and computing an overall p-value score.
International Drug Development Institute | Date: 2016-03-21
A method for central monitoring of a research trial utilizing a plurality of distributed data collection centers includes creating and storing a database consisting of datasets generated during the research trial. Statistical tests are executed in the network on a data collection center by data collection center basis to detect abnormalities and patterns present in datasets of the statistical database. A matrix containing p-values based upon the executed statistical tests is created and stored in the network. The matrix has as many rows as there are data collection centers and as many columns as executed statistical tests. Any outlying data collection centers are identified by summarizing the p-values. Data Inconsistency Score (DIS) is created for each collection center.
International Drug Development Institute | Date: 2012-04-20
A method for central monitoring of a research trial includes the steps of creating and storing a clinical database consisting of datasets generated during the research trial, preprocessing the database to remove variables that are unsuitable for analysis, extracting metadata from the database to identify types of the variables, storing the preprocessed datasets and corresponding metadata in a statistical database, executing statistical tests on a data collection center by data collection center basis to detect abnormalities and patterns present in datasets, creating and storing a matrix containing p-values based upon the executed statistical tests, identifying any outlying data collection centers by summarizing the p-values, determining if any of the executed statistical tests are faulty and removing such faulty executed statistical tests from the matrix to create a filtered matrix, and computing an overall p-value score.