Confounding factors in exposure–response analyses and mitigation strategies for monoclonal antibodies in oncology
- Dose selection and optimization is crucial in drug development to maximize benefits for all patients.
- Exposure–response (E-R) analysis is useful for dose-selection strategy, but in oncology, prognostic factors can confound the analysis, especially for monoclonal antibodies.
- The review addresses three approaches to mitigate confounding in oncology E-R analyses:
- Cox-proportional hazards modelling and case-matching
- Tumour growth inhibition–overall survival modelling
- Multiple dose level study design
- Studying multiple dose levels can reveal true E-R relationships but is impractical for pivotal trials in oncology.
- Focus is on the strengths and weaknesses of the first two approaches, highlighting the utility of tumour growth inhibition–overall survival modelling.
- The review critiques the reliance on E-R analyses from single dose level trials and suggests designing trials to study more dose levels earlier in the development process.
While contemporary drug development in oncology strives to deliver novel therapies to patients rapidly, it is also important to optimize dosing regimens to improve patient-centered care. Doses selected for pivotal trials may be efficacious doses, but not necessarily optimal to minimizing toxicity and maximizing clinical efficacy for all patients. Exposure–response (E-R) analysis is an approach that is used to support dose selection by characterizing the relationship between drug concentrations, efficacy, and safety. A variety of E-R analyses have supported dose labeling of many approved oncology drugs. Among the oncology therapies, however, additional complexity has been observed in characterizing E-R relationships for monoclonal antibodies. Specifically, prognostic factors can impact both pharmacokinetics (PK) and efficacy. This may result in a correlation between exposure and outcome that does not represent a causal E-R relationship and therefore, may not provide a useful basis for dose recommendations.
This was exemplified by the HELOISE trial (NCT01450696) of trastuzumab, which was conducted as part of a post-marketing requirement. Following the phase 3 trial ToGA (NCT01041404), trastuzumab was approved in combination with chemotherapy for first-line treatment of HER2-positive advanced gastric cancer. An E-R analysis, however, found that the patients in the lowest exposure quartile had an overall survival (OS) approximately 8 months shorter than those with higher exposures. This suggested that increasing trastuzumab exposure in this low-exposure subgroup may improve survival benefit, and thus supported the requirement of conducting a post-marketing trial for a higher dose. For this requirement, in the HELOISE trial, a higher trastuzumab dose was compared with the labeled dose in a population with similar prognostic factors as the low-exposure subgroup of the ToGA trial. Despite reliably increasing exposure, the higher dose did not improve OS in patients. This discrepancy between the results of the E-R analysis and the HELOISE trial indicates confounding in E-R analyses of monoclonal antibodies at a single dose level in oncology.
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