Literature DB >> 24419130

Nomogram to predict cycle-one serious drug-related toxicity in phase I oncology trials.

David M Hyman1, Anne A Eaton, Mrinal M Gounder, Gary L Smith, Erika G Pamer, Martee L Hensley, David R Spriggs, Percy Ivy, Alexia Iasonos.   

Abstract

PURPOSE: All patients in phase I trials do not have equivalent susceptibility to serious drug-related toxicity (SDRT). Our goal was to develop a nomogram to predict the risk of cycle-one SDRT to better select appropriate patients for phase I trials. PATIENTS AND METHODS: The prospectively maintained database of patients with solid tumor enrolled onto Cancer Therapeutics Evaluation Program-sponsored phase I trials activated between 2000 and 2010 was used. SDRT was defined as a grade ≥ 4 hematologic or grade ≥ 3 nonhematologic toxicity attributed, at least possibly, to study drug(s). Logistic regression was used to test the association of candidate factors to cycle-one SDRT. A final model, or nomogram, was chosen based on both clinical and statistical significance and validated internally using a bootstrapping technique and externally in an independent data set.
RESULTS: Data from 3,104 patients enrolled onto 127 trials were analyzed to build the nomogram. In a model with multiple covariates, Eastern Cooperative Oncology Group performance status, WBC count, creatinine clearance, albumin, AST, number of study drugs, biologic study drug (yes v no), and dose (relative to maximum administered) were significant predictors of cycle-one SDRT. All significant factors except dose were included in the final nomogram. The model was validated both internally (bootstrap-adjusted concordance index, 0.60) and externally (concordance index, 0.64).
CONCLUSION: This nomogram can be used to accurately predict a patient's risk for SDRT at the time of enrollment. Excluding patients at high risk for SDRT should improve the safety and efficiency of phase I trials.

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Year:  2014        PMID: 24419130      PMCID: PMC3918535          DOI: 10.1200/JCO.2013.49.8808

Source DB:  PubMed          Journal:  J Clin Oncol        ISSN: 0732-183X            Impact factor:   44.544


  15 in total

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Journal:  Ann N Y Acad Sci       Date:  2001-12       Impact factor: 5.691

2.  Defining the risk of toxicity in phase I oncology trials of novel molecularly targeted agents: a single centre experience.

Authors:  L R Molife; S Alam; D Olmos; M Puglisi; K Shah; R Fehrmann; L Trani; A Tjokrowidjaja; J S de Bono; U Banerji; S B Kaye
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Review 3.  Life-expectancy of patients enrolled in phase 1 clinical trials: a systematic review of published prognostic models.

Authors:  Anne Ploquin; David Olmos; Charles Ferté; Philippe A Cassier; Andrew Kramar; Alain Duhamel; Nicolas Penel
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Review 4.  How to build and interpret a nomogram for cancer prognosis.

Authors:  Alexia Iasonos; Deborah Schrag; Ganesh V Raj; Katherine S Panageas
Journal:  J Clin Oncol       Date:  2008-03-10       Impact factor: 44.544

Review 5.  Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors.

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6.  Risk of serious toxicity in 1181 patients treated in phase I clinical trials of predominantly targeted anticancer drugs: the M. D. Anderson Cancer Center experience.

Authors:  J J Wheler; A M Tsimberidou; D S Hong; A Naing; G S Falchook; S Fu; S Moulder; B Stephen; S Wen; R Kurzrock
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7.  Identification of factors limiting patient recruitment into phase I trials: a study from the Royal Marsden Hospital.

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Journal:  Br J Cancer       Date:  2012-08-21       Impact factor: 7.640

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  24 in total

1.  Beyond the dose-limiting toxicity period: Dermatologic adverse events of patients on phase 1 trials of the Cancer Therapeutics Evaluation Program.

Authors:  Alexander Drilon; Anne A Eaton; Katja Schindler; Mrinal M Gounder; David R Spriggs; Pamela Harris; S Percy Ivy; Alexia Iasonos; Mario E Lacouture; David M Hyman
Journal:  Cancer       Date:  2016-02-24       Impact factor: 6.860

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4.  The role of age on dose-limiting toxicities in phase I dose-escalation trials.

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Review 5.  Challenges Facing Early Phase Trials Sponsored by the National Cancer Institute: An Analysis of Corrective Action Plans to Improve Accrual.

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6.  Effect of Renal Dysfunction on Toxicity in Three Decades of Cancer Therapy Evaluation Program-Sponsored Single-Agent Phase I Studies.

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7.  A preoperative personalized risk assessment calculator for elderly ovarian cancer patients undergoing primary cytoreductive surgery.

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8.  Improving survival prediction using a novel feature selection and feature reduction framework based on the integration of clinical and molecular data.

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9.  Evaluation of the Safety and Benefit of Phase I Oncology Trials for Patients With Primary CNS Tumors.

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Journal:  J Clin Oncol       Date:  2015-08-17       Impact factor: 44.544

Review 10.  Prognostication of Survival in Patients With Advanced Cancer: Predicting the Unpredictable?

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Journal:  Cancer Control       Date:  2015-10       Impact factor: 3.302

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