Longitudinal patient-reported outcomes on genotype-guided irinotecan dosing: feasibility and clinical relevance.

INTRODUCTION: Standard investigator-based adverse events (AE) assessment is via CTCAE for clinical trials. However, including the patient perspective through PRO (patient-reported outcomes) enhances clinicians' understanding of patient toxicity and fosters early detection of AEs. We assessed longitudinal integration of PRO-CTCAE within clinical workflow in a phase II trial. MATERIALS AND METHODS: As a sub-study in a phase II trial of genotype-directed irinotecan dosing evaluating efficacy in patients with metastatic colorectal cancer receiving FOLFIRI and bevacizumab, patients reported on 13 AEs generating a PRO-CTCAE form. The primary objective was to estimate forms completed by patients and clinicians at least 80% of time. Secondary objectives were estimating concordance and time to first score of specific symptoms between patient and clinician pairs. RESULTS: Feasibility of longitudinal PRO-CTCAE integration was met as 96% of patients and clinician-patient pairs completed at least 80% of PRO-CTCAE forms available to them with 79% achieving 100% completion. Concordance between patient and clinician reporting a severe symptom was 73% with 24 disconcordant pairs, 21 involved patients who reported a severe symptom that the clinician did not. Although protocol-mandated dose reductions were guided by CTCAE not PRO-CTCAE responses, the median time to dose reduction of 2.53 months, and the time-to-event curve closely approximated time to patient-reported toxicity. CONCLUSION: Longitudinal integration of PRO-CTCAE paired CTCAE proved feasible. Compared to clinicians, patients reported severe symptoms more frequently and earlier. Patient-reported toxicity more closely aligned with dose decreases indicating incorporation into routine clinical practice may enhance early detection of toxicity improving patient safety and quality of life.

A phase II trial of UGT1A1 genotype-guided FOLFIRI plus bevacizumab as first-line therapy for advanced, unresectable colorectal cancer.

BACKGROUND: FOLFIRI is a standard regimen for metastatic colorectal cancer (mCRC). We hypothesized that a pharmacogenomic-directed strategy where more efficient irinotecan metabolizers (UGT1A1 *1/*1 homozygotes and *1/*28 heterozygotes) receive higher-than-standard irinotecan doses would improve progression-free survival (PFS) compared to non-genotype selected historical controls with acceptable toxicity. METHODS: In this phase II multicenter study irinotecan dosing in first-line FOLFIRI and bevacizumab for mCRC was based on UGT1A1 genotype with *1/*1, *1/*28, and *28/*28 patients receiving 310 mg/m2, 260 mg/m2, and 180 mg/m2, respectively. Primary endpoint was PFS. Secondary endpoints were investigator and patient-reported adverse events, and estimation of overall survival (OS). RESULTS: One-hundred patients were enrolled with 91 evaluable for PFS and 83 evaluable for best response. Median PFS was 12.5 months (90% CI 10.9, 15.4), shorter than the anticipated alternative hypothesis of 14 months. PFS by genotype was 12.5 months (90% CI 10.9, 17.4) for *1/*1, 14.6 months (90% CI 11.8, 17.5) for *1/*28, and 6 months (90% CI 2.3, 7.7) for *28/28, respectively. OS was 24.5 months (90% CI 19.1, 30.7) and by genotype was 26.5 (90% CI 19.1, 32.9), 25.9 (90% CI 17.6, 37.7), and 13.4 (90% CI 2.3, 20.5) months for *1/*1, *1/*28, and *28/*28, respectively. G3/4 toxicity was similar between all subgroups, including diarrhea and neutropenia. CONCLUSIONS: A pharmacogenomic-directed irinotecan strategy improved PFS in the *1/*1 and *1/*28 genotypes with higher rates of neutropenia and similar rates of diarrhea compared to expected with standard FOLFIRI dosing. However, improvements in response rate and PFS were modest. This strategy should not change standard practice for mCRC patients in the first-line setting.

Accuracy and consistency of publicly available Large Language Models as clinical decision support tools for the management of colon cancer.

BACKGROUND: Large Language Models (LLM; e.g., ChatGPT) may be used to assist clinicians and form the basis of future clinical decision support (CDS) for colon cancer. The objectives of this study were to (1) evaluate the response accuracy of two LLM-powered interfaces in identifying guideline-based care in simulated clinical scenarios and (2) define response variation between and within LLMs. METHODS: Clinical scenarios with "next steps in management" queries were developed based on National Comprehensive Cancer Network guidelines. Prompts were entered into OpenAI ChatGPT and Microsoft Copilot in independent sessions, yielding four responses per scenario. Responses were compared to clinician-developed responses and assessed for accuracy, consistency, and verbosity. RESULTS: Across 108 responses to 27 prompts, both platforms yielded completely correct responses to 36% of scenarios (n = 39). For ChatGPT, 39% (n = 21) were missing information and 24% (n = 14) contained inaccurate/misleading information. Copilot performed similarly, with 37% (n = 20) having missing information and 28% (n = 15) containing inaccurate/misleading information (p = 0.96). Clinician responses were significantly shorter (34 ± 15.5 words) than both ChatGPT (251 ± 86 words) and Copilot (271 ± 67 words; both p < 0.01). CONCLUSIONS: Publicly available LLM applications often provide verbose responses with vague or inaccurate information regarding colon cancer management. Significant optimization is required before use in formal CDS.

Quality of Life Outcomes in Stage IV Colorectal Cancer.

With improvements across the colorectal cancer care continuum, from screening and earlier detection to better systemic options, patients are living longer with the disease. Given these improvements over the last several decades, quality of life outcomes have become important components when evaluating treatment efficacy and adverse effects. This article reviews quality of life measurement generally, discusses tools currently being used in colorectal cancer patients, and reviews outcomes following both surgical and nonsurgical management from clinical trials, observational studies, and meta-analyses.

Molecular insights into clinical trials for immune checkpoint inhibitors in colorectal cancer: Unravelling challenges and future directions.

Colorectal cancer (CRC) is a complex disease with diverse etiologies and clinical outcomes. Despite considerable progress in development of CRC therapeutics, challenges remain regarding the diagnosis and management of advanced stage metastatic CRC (mCRC). In particular, the five-year survival rate is very low since mCRC is currently rarely curable. Over the past decade, cancer treatment has significantly improved with the introduction of cancer immunotherapies, specifically immune checkpoint inhibitors. Therapies aimed at blocking immune checkpoints such as PD-1, PD-L1, and CTLA-4 target inhibitory pathways of the immune system, and thereby enhance anti-tumor immunity. These therapies thus have shown promising results in many clinical trials alone or in combination. The efficacy and safety of immunotherapy, either alone or in combination with CRC, have been investigated in several clinical trials. Clinical trials, including KEYNOTE-164 and CheckMate 142, have led to Food and Drug Administration approval of the PD-1 inhibitors pembrolizumab and nivolumab, respectively, for the treatment of patients with unresectable or metastatic microsatellite instability-high or deficient mismatch repair CRC. Unfortunately, these drugs benefit only a small percentage of patients, with the benefits of immunotherapy remaining elusive for the vast majority of CRC patients. To this end, primary and secondary resistance to immunotherapy remains a significant issue, and further research is necessary to optimize the use of immunotherapy in CRC and identify biomarkers to predict the response. This review provides a comprehensive overview of the clinical trials involving immune checkpoint inhibitors in CRC. The underlying rationale, challenges faced, and potential future steps to improve the prognosis and enhance the likelihood of successful trials in this field are discussed.