I-38 Aliénor Bergès

Importance of Quantifying Neutropenia Risk Factors in Phase I Solid Malignancy Dose Finding; A Simulation Case

Alienor Berges, Martin Johnson and Alexander MacDonald

Quantitative Clinical Pharmacology, Early Clinical Development, IMED Biotech Unit, AstraZeneca, Cambridge, UK

Background

In Oncology drug development, the primary objective of most phase I clinical dose finding studies continues to be identification of a maximum tolerated dose (MTD): a dose/regimen found to have limited  “dose‐limiting toxicities (DLT)”, in a small group of patients (typically ≤ 1 out of 6), over a finite period of time (usually 21-28 days following treatment). The scientific and statistical limitations of this approach are well-documented [1].  However, patient characteristics, such as cancer type, health status or prior anti-cancer therapy, may influence the MTD identified in these studies. We have previously reviewed the risk factors for neutrophil toxicity in cancer populations [2], a common DLT in phase I studies, and Lyman et al. have attempted to quantify risk of neutropenic complications in patients undergoing chemotherapy [3].

We present a simulation study to assess the effect of various degrees of patient’s risk to dose-limiting neutropenic complications (represented by severe or febrile neutropenia (SN/FB)) on the MTD of a theoretical anti-cancer agent.

Methods

We used a logistic regression model that includes i) background risk , ii) patient’s risk prior to treatment and based on the patient’s specific risk factors Xi=1,2,…m and iii) dose-related drug effect toxicity.

Logit(pSN/FB) = a + b1 * X1 + … + bm * Xm + C * DOSE

The probability of neutropenia (pSN/FB) was calculated from Logit(pSN/FB) and binary individual SN/FB events (DV=1 if presence or DV=0 if absence) were generated according to a binomial distribution given pSN/FB and a sample size per group. The binomial distribution led to natural variability in the toxicity for a given dose, in a given patient among the simulations.

The simulations were generated based on a typical dose escalation study design: 5 dose levels (0.1, 1, 3, 6 and 9 mg) and 6 patients per dose group. Four scenarios were selected, based on drug toxicity and patient’s risk prior to treatment:

  • Low and high-toxicity drug, with a parameter value such as pSN/FB at the top dose was associated to 0.5 and 0.9 respectively;
  • Low and high-risk population, with a combination of risk factors Xi such as pSN/FB prior to treatment was associated to 0.05 and 0.25 respectively. The risk factors and their regression coefficient values bi were obtained from the risk model from Lyman et al. [3]

For each study, 1000 replicates were simulated to obtain the predictive distribution of MTD values. The simulations were performed in R software (version 3.5.1). Count of SN/FB events was calculated from the simulated individual SN/FB events per dose group, and MTD was determine per study using the operational definition.

Results

Based on Lyman model [3], we simulated two sets of patient’s characteristics; one associated with the low-risk population (age <65 years, breast tumor, no prior chemotherapy, normal white blood cell and normal liver enzymes) and one associated with the high-risk population (age ≥65 years, small-cell lung cancer, prior chemotherapy, low white blood cell and elevated liver enzymes). 

The distributions of MTD values were significantly different between the low and the high-risk populations. For the low-toxicity drug, the most likely MTD was at the high doses (9 mg and above) in the low-risk population, and at the low doses (0.1 and 1 mg) in the high-risk population. For the high-toxicity drug, the most likely MTDs in low-risk population and high-risk population were up to 6 mg and up to 1 mg respectively.  

Additional simulations using other risk models from literature are planned to investigate the MTD impact for other risk factors and/or other degrees of correlation. In addition, trials combining low and high-risk patients would give a more representative Phase I patients population.

Conclusion

Those simulations including baseline patient’s risks, reveal a clear shift in the MTD distributions between the low and high-risk populations, irrespective of the level of drug toxicity. Although those simulated cases are the extreme SN/FB predicted risks, they illustrate the importance of accounting for risk factors in the MTD concept, determination and application for dose finding.

References:
[1]. Symposium. Challenging the maximum tolerated dosing paradigm in oncology: Threading the needle with targeted agents. ASCPT Annual Meeting (Atlanta, GA, March 2014).
[2]. Casabianca et al. Literature Review to Explore the Risk Factors of Neutrophil Toxicity in Oncology. PKUK conference November 2018
[3]. Lyman et al. Predicting Individual Risk of Neutropenic Complications in Patients Receiving Cancer Chemotherapy Cancer. 2011 May 1; 117(9): 1917–1927

Reference: PAGE 28 (2019) Abstr 8857 [www.page-meeting.org/?abstract=8857]

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