Toxicity Attribution in Phase I Trials: Evaluating the Effect of Dose on the Frequency of Related and Unrelated Toxicities

Abstract

Background Phase I studies rely on investigators to accurately attribute of adverse events as related or unrelated to study drug. This information is ultimately used to help establish a safe dose. Patterns of physician attribution in the Phase I setting have 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. Methods Individual patient records from 38 Phase I studies activated between 2000-2010 were used. Dose was defined as percent 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) while related toxicity increased with dose (p<0.0001, both grade ≥3 and ≥1). Similar results were observed across toxicity categories. In the 5-tier system, toxicities attributed as ‘possibly’, &lsquo;probably’, or ‘definitely’ related were associated with dose (all p<0.0001) while 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 which 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 2-tier system by collapsing ‘possibly’, ‘probably’, and ‘definitely’ related.

Pharmacogenomics‐Based Point‐of‐Care Clinical Decision Support Significantly Alters Drug Prescribing

“…At least 20% of all final scores were also rated by at least two independent raters to ensure agreement (κ ≥ 0.95), and any disagreeing scores were reviewed by a third reviewer until consensus. We categorized medication changes with scores ≥4 as “influenced by pharmacogenomic information” for the subsequent analyses—a conservative cutoff that was even more stringent than that used in clinical trials for ascribing adverse drug events(49). …”

Calcitriol and cancer therapy: A missed opportunity

“…In 2011 Le Tourneau and colleagues analyzed 155 phase I trials and found that “hypercalcemia” was not specifically noted to have been a DLT in any study, though electrolyte abnormalities were the defining DLT in <5% of trials. Overall, the great majority of studies employed greater than or equal to grade 3 toxicity as a DLT definition, supporting the observation that the MTD and DLT delineation for DN-101 was conservative ( Eaton et al, 2016 ; Le Tourneau et al, 2011 ). In a trial of weekly intravenous calcitriol + gefitinib and fixed dose dexamethasone, Muindi and colleagues defined DLT as any of the following toxicities attributable to study treatment in the first 4 weeks of treatment: ≥3 or 4 toxicity except for grade 3 anemia, ≥grade 2 or above hypercalcemia (corrected calcium > 11.5 mg/dL) if confirmed on repeat blood draw (>72 h), any grade 2 or above hypercalcemia that is associated with serious hypercalcemic symptoms, any treatment interruption that lasts for >2 weeks that is related to treatment toxicity, sustained increase (>72 h) in creatinine to >2× baseline and >2 mg/dL, and clinical or radiological evidence of new genitourinary stones.…”

Phase I Designs That Allow for Uncertainty in the Attribution of Adverse Events

“…modifying the dose escalation as a result of counting certain toxicities as DLTs that, in fact, are not related to the treatment. Type A errors are likely to be much smaller and, in many cases, may be considered to be negligible (Eaton et al ., ).…”

“…Eaton et al . () attempted to quantify this problem by estimating the dose–toxicity curve by using data from phase I trials and Sharma and Ratain () concluded that ‘a probability estimation would better support dose selection’.…”