Toxicity attribution in phase I trials: Evaluating the effect of dose on the frequency of related and unrelated toxicities Journal Article

Authors: Eaton, A.; Iasonos, A.; Gounder, M. M.; Pamer, E. G.; Drilon, A.; Vulih, D.; Smith, G. L.; Ivy, S. P.; Spriggs, D. R.; Hyman, D. M.
Article Title: Toxicity attribution in phase I trials: Evaluating the effect of dose on the frequency of related and unrelated toxicities
Abstract: Purpose: Phase I studies rely on investigators to accurately attribute adverse events as related or unrelated to study drug. This information is ultimately used to help establish a safe dose. Attribution in the phase I setting has not been widely studied and assessing the accuracy of attribution is complicated by the lack of a gold standard. We examined dose?toxicity relationships as a function of attribution and toxicity category to evaluate for evidence of toxicity misattribution. Experimental Design: Individual patient records from 38 phase I studies activated between 2000 and 2010 were used. Dose was defined as a percentage of maximum dose administered on each study. Relationships between dose and patient-level toxicity were explored graphically and with logistic regression. All P values were two-sided. Results: 11,909 toxicities from 1,156 patients were analyzed. Unrelated toxicity was not associated with dose (P = 0.0920 for grade ≥3, P = 0.4194 for grade ≥1), whereas related toxicity increased with dose (P < 0.0001, both grade ≥3 and ≥1). Similar results were observed across toxicity categories. In the five-tier system, toxicities attributed as "possibly," "probably," or "definitely" related were associated with dose (all P < 0.0001), whereas toxicities attributed as "unlikely" or "unrelated" were not (all P > 0.1). Conclusions: Reassuringly, we did not observe an association between unrelated toxicity rate and dose, an association that could only have been explained by physician misattribution. Our findings also confirmed our expectation that related toxicity rate increases with dose. Our analysis supports simplifying attribution to a two-tier system by collapsing "possibly," "probably," and "definitely" related. © 2015 American Association for Cancer Research.
Journal Title: Clinical Cancer Research
Volume: 22
Issue: 3
ISSN: 1078-0432
Publisher: American Association for Cancer Research  
Date Published: 2016-02-01
Start Page: 553
End Page: 559
Language: English
DOI: 10.1158/1078-0432.ccr-15-0339
PROVIDER: scopus
PUBMED: 26324741
PMCID: PMC4819316
Notes: Article -- Export Date: 4 April 2016 -- Source: Scopus
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MSK Authors
  1. Alexia Elia Iasonos
    179 Iasonos
  2. Mrinal M Gounder
    68 Gounder
  3. David Hyman
    181 Hyman
  4. Anne Austin Eaton
    115 Eaton
  5. David R Spriggs
    309 Spriggs
  6. Alexander Edward Drilon
    136 Drilon
  7. Erika   Pamer
    7 Pamer