Dataset Information

Resistance prediction in AML: analysis of 4601 patients from MRC/NCRI, HOVON/SAKK, SWOG and MD Anderson Cancer Center.

ABSTRACT: Therapeutic resistance remains the principal problem in acute myeloid leukemia (AML). We used area under receiver-operating characteristic curves (AUCs) to quantify our ability to predict therapeutic resistance in individual patients, where AUC=1.0 denotes perfect prediction and AUC=0.5 denotes a coin flip, using data from 4601 patients with newly diagnosed AML given induction therapy with 3+7 or more intense standard regimens in UK Medical Research Council/National Cancer Research Institute, Dutch-Belgian Cooperative Trial Group for Hematology/Oncology/Swiss Group for Clinical Cancer Research, US cooperative group SWOG and MD Anderson Cancer Center studies. Age, performance status, white blood cell count, secondary disease, cytogenetic risk and FLT3-ITD/NPM1 mutation status were each independently associated with failure to achieve complete remission despite no early death ('primary refractoriness'). However, the AUC of a bootstrap-corrected multivariable model predicting this outcome was only 0.78, indicating only fair predictive ability. Removal of FLT3-ITD and NPM1 information only slightly decreased the AUC (0.76). Prediction of resistance, defined as primary refractoriness or short relapse-free survival, was even more difficult. Our limited ability to forecast resistance based on routinely available pretreatment covariates provides a rationale for continued randomization between standard and new therapies and supports further examination of genetic and posttreatment data to optimize resistance prediction in AML.

SUBMITTER: Walter RB

PROVIDER: S-EPMC4318722 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature

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Resistance prediction in AML: analysis of 4601 patients from MRC/NCRI, HOVON/SAKK, SWOG and MD Anderson Cancer Center.

Walter R B RB Othus M M Burnett A K AK Löwenberg B B Kantarjian H M HM Ossenkoppele G J GJ Hills R K RK Ravandi F F Pabst T T Evans A A Pierce S R SR Vekemans M-C MC Appelbaum F R FR Estey E H EH

Leukemia 20140812 2

Therapeutic resistance remains the principal problem in acute myeloid leukemia (AML). We used area under receiver-operating characteristic curves (AUCs) to quantify our ability to predict therapeutic resistance in individual patients, where AUC=1.0 denotes perfect prediction and AUC=0.5 denotes a coin flip, using data from 4601 patients with newly diagnosed AML given induction therapy with 3+7 or more intense standard regimens in UK Medical Research Council/National Cancer Research Institute, Du ...[more]

PMID: 25113226

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Project description:BackgroundMen diagnosed with prostate cancer are at risk for competing morbidity and mortality due to cardiometabolic disease given their advanced age at diagnosis, high prevalence of pre-existing risk factors, and receipt of systemic therapy that targets the androgen receptor (AR). Expert panels have stressed the importance of cardiometabolic risk assessment in the clinic and proposed evaluating key risks using consensus paradigms. Yet, there is a gap in real-world evidence for implementation of comprehensive cardiometabolic care for men with prostate cancer.MethodsThis is a retrospective, descriptive study of patients with prostate cancer who were referred and evaluated in the Healthy Heart Program at MD Anderson Cancer Center, which was established to mitigate cardiometabolic risks in men with prostate cancer. Patients were seen by a cardiologist and exercise physiologist to evaluate and manage cardiometabolic risk factors, including blood pressure, cholesterol, blood glucose, tobacco use, and coronary artery disease, concurrent with management of their cancer by a medical oncologist.ResultsFrom December 2018 through October 2021, the Healthy Heart Program enrolled 55 men with prostate cancer, out of which 35 had biochemical, locoregional recurrence or distant metastases, while all received at least a single dose of a luteinizing hormone-releasing hormone (LHRH) analog. Ninety-three percent of men were overweight or obese, and 51% had an intermediate or high risk of atherosclerotic cardiovascular disease at 10 years based on the pooled cohort equation. Most men had an overlap of two or more cardiometabolic diseases (84%), and 25% had an overlap of at least 4 cardiometabolic diseases. Although uncontrolled hypertension and hyperlipidemia were common among the cohort (45% and 26%, respectively), only 29% of men followed up with the clinic.ConclusionsMen with prostate cancer have a high burden of concurrent cardiometabolic risk factors. At a tertiary cancer center, the Healthy Heart Program was implemented to address this need, yet the utility of the program was limited by poor follow-up possibly due to outside cardiometabolic care and inconvenient appointment logistics, a lack of cardiometabolic labs at the time of visits, and telemedicine visits.

Project description:BACKGROUND/AIMS:In our 2009 article, we showed that Bayesian methods had established a foothold in developing therapies in our institutional oncology trials. In this article, we will document what has happened since that time. In addition, we will describe barriers to implementing Bayesian clinical trials, as well as our experience overcoming them. METHODS:We reviewed MD Anderson Cancer Center clinical trials submitted to the institutional protocol office for scientific and ethical review between January 2009 and December 2013, the same length time period as the previous article. We tabulated Bayesian methods implemented for design or analyses for each trial and then compared these to our previous findings. RESULTS:Overall, we identified 1020 trials and found that 283 (28%) had Bayesian components so we designated them as Bayesian trials. Among MD Anderson-only and multicenter trials, 56% and 14%, respectively, were Bayesian, higher rates than our previous study. Bayesian trials were more common in phase I/II trials (34%) than in phase III/IV (6%) trials. Among Bayesian trials, the most commonly used features were for toxicity monitoring (65%), efficacy monitoring (36%), and dose finding (22%). The majority (86%) of Bayesian trials used non-informative priors. A total of 75 (27%) trials applied Bayesian methods for trial design and primary endpoint analysis. Among this latter group, the most commonly used methods were the Bayesian logistic regression model (N?=?22), the continual reassessment method (N?=?20), and adaptive randomization (N?=?16). Median institutional review board approval time from protocol submission was the same 1.4?months for Bayesian and non-Bayesian trials. Since the previous publication, the Biomarker-Integrated Approaches of Targeted Therapy for Lung Cancer Elimination (BATTLE) trial was the first large-scale decision trial combining multiple treatments in a single trial. Since then, two regimens in breast cancer therapy have been identified and published from the cooperative Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis (I-SPY 2), enhancing cooperation among investigators and drug developers across the nation, as well as advancing information needed for personalized medicine. Many software programs and Shiny applications for Bayesian trial design and calculations are available from our website which has had more than 21,000 downloads worldwide since 2004. CONCLUSION:Bayesian trials have the increased flexibility in trial design needed for personalized medicine, resulting in more cooperation among researchers working to fight against cancer. Some disadvantages of Bayesian trials remain, but new methods and software are available to improve their function and incorporation into cancer clinical research.

Dataset Information

Resistance prediction in AML: analysis of 4601 patients from MRC/NCRI, HOVON/SAKK, SWOG and MD Anderson Cancer Center.

Publications

Resistance prediction in AML: analysis of 4601 patients from MRC/NCRI, HOVON/SAKK, SWOG and MD Anderson Cancer Center.

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