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Monitoring late-onset toxicities in phase I trials using predicted risks.

ABSTRACT: Late-onset (LO) toxicities are a serious concern in many phase I trials. Since most dose-limiting toxicities occur soon after therapy begins, most dose-finding methods use a binary indicator of toxicity occurring within a short initial time period. If an agent causes LO toxicities, however, an undesirably large number of patients may be treated at toxic doses before any toxicities are observed. A method addressing this problem is the time-to-event continual reassessment method (TITE-CRM, Cheung and Chappell, 2000). We propose a Bayesian dose-finding method similar to the TITE-CRM in which doses are chosen using time-to-toxicity data. The new aspect of our method is a set of rules, based on predictive probabilities, that temporarily suspend accrual if the risk of toxicity at prospective doses for future patients is unacceptably high. If additional follow-up data reduce the predicted risk of toxicity to an acceptable level, then accrual is restarted, and this process may be repeated several times during the trial. A simulation study shows that the proposed method provides a greater degree of safety than the TITE-CRM, while still reliably choosing the preferred dose. This advantage increases with accrual rate, but the price of this additional safety is that the trial takes longer to complete on average.

SUBMITTER: Bekele BN

PROVIDER: S-EPMC3294317 | biostudies-literature | 2008 Jul

REPOSITORIES: biostudies-literature

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Monitoring late-onset toxicities in phase I trials using predicted risks.

Bekele B Nebiyou BN Ji Yuan Y Shen Yu Y Thall Peter F PF

Biostatistics (Oxford, England) 20071214 3

Late-onset (LO) toxicities are a serious concern in many phase I trials. Since most dose-limiting toxicities occur soon after therapy begins, most dose-finding methods use a binary indicator of toxicity occurring within a short initial time period. If an agent causes LO toxicities, however, an undesirably large number of patients may be treated at toxic doses before any toxicities are observed. A method addressing this problem is the time-to-event continual reassessment method (TITE-CRM, Cheung ...[more]

PMID: 18084008

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Project description:ObjectivesPrediction of late-onset sepsis (onset beyond day 3 of life) in preterm infants, based on multiple patient monitoring signals 24 hours before onset.DesignContinuous high-resolution electrocardiogram and respiration (chest impedance) data from the monitoring signals were extracted and used to create time-interval features representing heart rate variability, respiration, and body motion. For each infant with a blood culture-proven late-onset sepsis, a Cultures, Resuscitation, and Antibiotics Started Here moment was defined. The Cultures, Resuscitation, and Antibiotics Started Here moment served as an anchor point for the prediction analysis. In the group with controls (C), an "equivalent crash moment" was calculated as anchor point, based on comparable gestational and postnatal age. Three common machine learning approaches (logistic regressor, naive Bayes, and nearest mean classifier) were used to binary classify samples of late-onset sepsis from C. For training and evaluation of the three classifiers, a leave-k-subjects-out cross-validation was used.SettingLevel III neonatal ICU.PatientsThe patient population consisted of 32 premature infants with sepsis and 32 age-matched control patients.InterventionsNo interventions were performed.Measurements and main resultsFor the interval features representing heart rate variability, respiration, and body motion, differences between late-onset sepsis and C were visible up to 5 hours preceding the Cultures, Resuscitation, and Antibiotics Started Here moment. Using a combination of all features, classification of late-onset sepsis and C showed a mean accuracy of 0.79 ± 0.12 and mean precision rate of 0.82 ± 0.18 3 hours before the onset of sepsis.ConclusionsInformation from routine patient monitoring can be used to predict sepsis. Specifically, this study shows that a combination of electrocardiogram-based, respiration-based, and motion-based features enables the prediction of late-onset sepsis hours before the clinical crash moment.

Project description:IntroductionThis study assessed baseline cardiovascular (CV) risk factors, concomitant CV medication use, risk of major adverse cardiac events-plus (MACE-plus), and bleeding adverse events (AEs) in patients with idiopathic pulmonary fibrosis (IPF) in three randomized, placebo-controlled phase III trials of pirfenidone.MethodsPatients in the pirfenidone phase III trials were included. Patients with unstable or deteriorating cardiac disease within 6 months before enrollment were ineligible. Medical history at baseline and concomitant CV medication use during treatment were reported. A retrospective, blinded review of AE preferred terms was conducted to identify MACE-plus and bleeding events. Subgroup analyses examined the impact of concomitant CV medication use on how pirfenidone treatment affected clinical outcomes.ResultsIn total, 1247 patients were included [n = 623 pirfenidone (2403 mg/day) and n = 624 placebo]. The median age was 68 years, 74% were male, and 65% were current/former smokers. Commonly reported CV risk factors included hypertension (52%), obesity (44%), hypercholesterolemia (23%), and hyperlipidemia (23%). Pre-existing cardiac disorders included coronary artery disease (16%), myocardial infarction (5%), and atrial fibrillation (5%). Lipid-modifying agents (60%), antithrombotic agents (54%), and renin-angiotensin inhibitors (39%) were commonly used concomitant CV medications. The incidences of MACE-plus and bleeding events were similar between the pirfenidone and placebo groups (1.8% and 2.9% for MACE-plus events and 3.7% and 4.3% for bleeding events, respectively). Except for patients receiving heparin, pirfenidone had a beneficial effect compared with placebo on efficacy outcomes regardless of concomitant CV medications.ConclusionsCV risk factors and comorbidities and use of concomitant CV medications are common in patients with IPF. Pirfenidone did not appear to increase the risk of CV or bleeding events. Use of several concomitant CV medications, including warfarin, did not appear to adversely impact pirfenidone's beneficial effect on efficacy outcomes.Trial registrationNCT00287716, NCT00287729, and NCT01366209.FundingF. Hoffmann-La Roche Ltd. and Genentech, Inc.

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Monitoring late-onset toxicities in phase I trials using predicted risks.

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Monitoring late-onset toxicities in phase I trials using predicted risks.

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