The National Cancer Institute Moonshot research initiative calls for improvements in the analysis and reporting of treatment toxicity to advise key stakeholders on treatment tolerability and inform regulatory and clinical decision making. This study illustrates alternative approaches to toxicity evaluation using the National Surgical Adjuvant Breast and Bowel Project R-04 clinical trial as an example. National Surgical Adjuvant Breast and Bowel Project R-04 was a neoadjuvant chemoradiation trial in stage II–III rectal cancer patients. A 2 x 2 factorial design was used to evaluate whether the addition of oxaliplatin (Oxa) to 5-fluorouracil (5FU) or capecitabine (Cape) with radiation therapy improved local-regional tumor control. The toxicity index (TI), which accounts for the frequency and severity of toxicities, was compared across treatments using multivariable probabilistic index models, where Pr A < B indicates the probability that higher values of TI were observed for A when compared with B. Baseline age, sex, performance status, body mass index, surgery type, and stage were evaluated as independent risk factors. A total of 4560 toxicities from 1558 patients were analyzed. Results from adjusted probabilistic index models indicate that oxaliplatin-containing regimens had statistically significant (P < .001) probability (Pr) for higher TI compared with regimens without oxaliplatin (Pr 5FU < 5FU + Oxa = 0.619, 95% confidence interval [CI] = 0.560 to 0.674; Pr 5FU < Cape + Oxa = 0.627, 95% CI = 0.568 to 0.682; Pr Cape < 5FU + Oxa = 0.587, 95% 0.527 to 0.644; and Pr Cape < Cape + Oxa = 0.596, 95% 0.536 to 0.653). When compared with other existing toxicity analysis methods, TI provided greater power to detect differences between treatments. This article uses standard data collected in a cancer clinical trial to introduce descriptive and analytic methods that account for the additional burden of multiple toxicities. These methods may provide a more accurate description of a patient’s treatment experience that could lead to individualized dosing for better toxicity control. Future research will evaluate the generalizability of these findings in trials with similar drugs.
Escalation with overdose control (EWOC) is a Bayesian adaptive phase I clinical trial design that produces consistent sequences of doses while controlling the probability that patients are overdosed. However, this design does not take explicitly into account the time it takes for a patient to exhibit dose limiting toxicity (DLT) since the occurrence of DLT is ascertained within a predetermined window of time. Models to estimate the Maximum Tolerated Dose (MTD) that use the exact time when the DLT occurs are expected to be more precise than those where the variable of interest is categorized as presence or absence of DLT, given that information is lost in the process of categorization of the variable. We develop a class of parametric models for time to toxicity data in order to estimate the MTD efficiently, and present extensive simulations showing that the method has good design operating characteristics relative to the original EWOC and a version of time to event EWOC (TITE-EWOC) which allocates weights to account for the time it takes for a patient to exhibit DLT. The methodology is exemplified by a cancer phase I clinical trial we designed in order to estimate the MTD of Veliparib (ABT-888) in combination with fixed doses of gemcitabine and intensity modulated radiation therapy in patients with locally advanced, un-resectable pancreatic cancer.
PURPOSE: To assess safety and immune biomarkers after preoperative radiation therapy (RT) and anti-PD1 therapy in breast cancer. MATERIALS AND METHODS: A phase I/IIb trial of pembrolizumab with RT was conducted in patients with triple-negative breast cancer (TNBC) and hormone receptor–positive/human epidermal growth factor receptor 2–negative (HR+/HER2–) breast cancer. All received pembrolizumab followed by a second cycle + RT (anti-PD1/RT) of 24 Gy/three daily fractions delivered to the breast tumor and then neoadjuvant chemotherapy (NAC). Blood and tumor biopsies were obtained at baseline, after anti-PD1, and after anti–PD-RT. Coprimary end points were safety and change in tumor-infiltrating lymphocytes (TILs). Secondary end points were pathologic complete response (pCR), residual cancer burden (RCB) rates, and event-free survival (EFS). RESULTS: Sixty-six patients with stage I-III breast cancer (54 TNBC, 12 HR+/HER2–) were enrolled. The median follow-up was 32 months. Safety end point was met. Incidence of grade ≥3 toxicities was 41%. The pCR rate was 59.2%, 33.3%, and 54.5% for the TNBC, HR+/HER2–, and entire cohort, respectively. A total of 77.8% of TNBC and 41.6% of HR+/HER2– had a near pCR (RCB 0-1). The 3-year EFS was 80%. In the entire cohort, PD-L1 expression increased after anti-PD1 (median Combined Positive Score [CPS], 7.49-23.20; 95% CI, –41.88 to –6.30; P = .044) and anti-PD1/RT (median CPS, 7.49-23.41; 95% CI, –41.88 to –6.30; P = .009), compared with baseline. In TNBC, adding RT to anti-PD1 significantly decreased TILs (28.9%-17.1%; 95% CI, 2.46 to 21.09; P = .014). Baseline TILs correlated with PD-L1 expression and TNF-a. CONCLUSION: Preoperative RT with pembrolizumab is safe and results in high pCR rates and 3-year EFS, despite the lack of pembrolizumab during NAC. PD-L1 and TILs may be predictive biomarkers for preoperative anti-PD1/RT response. Reduction in TILs after adding RT to anti-PD1 highlights the importance of treatment sequencing.