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Development and Assessment of a Clinical Calculator for Estimating the Likelihood of Recurrence and Survival Among Patients With Locally Advanced Rectal Cancer Treated With Chemotherapy, Radiotherapy, and Surgery

IMPORTANCE: Predicting outcomes in patients receiving neoadjuvant therapy for rectal cancer is challenging because of tumor downstaging. Validated clinical calculators that can estimate recurrence-free survival (RFS) and overall survival (OS) among patients with rectal cancer who have received multi...

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Detalles Bibliográficos
Autores principales: Weiser, Martin R., Chou, Joanne F., Keshinro, Ajaratu, Chapman, William C., Bauer, Philip S., Mutch, Matthew G., Parikh, Parag J., Cercek, Andrea, Saltz, Leonard B., Gollub, Marc J., Romesser, Paul B., Crane, Christopher H., Shia, Jinru, Markowitz, Arnold J., Garcia-Aguilar, Julio, Gönen, Mithat
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Association 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8576585/
https://www.ncbi.nlm.nih.gov/pubmed/34748003
http://dx.doi.org/10.1001/jamanetworkopen.2021.33457
Descripción
Sumario:IMPORTANCE: Predicting outcomes in patients receiving neoadjuvant therapy for rectal cancer is challenging because of tumor downstaging. Validated clinical calculators that can estimate recurrence-free survival (RFS) and overall survival (OS) among patients with rectal cancer who have received multimodal therapy are needed. OBJECTIVE: To develop and validate clinical calculators providing estimates of rectal cancer recurrence and survival that are better for individualized decision-making than the American Joint Committee on Cancer (AJCC) staging system or the neoadjuvant rectal (NAR) score. DESIGN, SETTING, AND PARTICIPANTS: This prognostic study developed risk models, graphically represented as nomograms, for patients with incomplete pathological response using Cox proportional hazards and multivariable regression analyses with restricted cubic splines. Because patients with complete pathological response to neoadjuvant therapy had uniformly favorable outcomes, their predictions were obtained separately. The study included 1400 patients with stage II or III rectal cancer who received treatment with chemotherapy, radiotherapy, and surgery at 2 comprehensive cancer centers (Memorial Sloan Kettering [MSK] Cancer Center and Siteman Cancer Center [SCC]) between January 1, 1998, and December 31, 2017. Patients from the MSK cohort received chemoradiation, surgery, and adjuvant chemotherapy from January 1, 1998, to December 31, 2014; these patients were randomly assigned to either a model training group or an internal validation group. Models were externally validated using data from the SCC cohort, who received either chemoradiation, surgery, and adjuvant chemotherapy (chemoradiotherapy group) or short-course radiotherapy, consolidation chemotherapy, and surgery (total neoadjuvant therapy with short-course radiotherapy group) from January 1, 2009, to December 31, 2017. Data were analyzed from March 1, 2020, to January 10, 2021. EXPOSURES: Chemotherapy, radiotherapy, chemoradiotherapy, and surgery. MAIN OUTCOMES AND MEASURES: Recurrence-free survival and OS were the outcome measures, and the discriminatory performance of the clinical calculators was measured with concordance index and calibration plots. The ability of the clinical calculators to predict RFS and OS was compared with that of the AJCC staging system and the NAR score. The models for RFS and OS among patients with incomplete pathological response included postoperative pathological tumor category, number of positive lymph nodes, tumor distance from anal verge, and large- and small-vessel venous and perineural invasion; age was included in the risk model for OS. The final clinical calculators provided RFS and OS estimates derived from Kaplan-Meier curves for patients with complete pathological response and from risk models for patients with incomplete pathological response. RESULTS: Among 1400 total patients with locally advanced rectal cancer, the median age was 57.8 years (range, 18.0-91.9 years), and 863 patients (61.6%) were male, with tumors at a median distance of 6.7 cm (range, 0-15.0 cm) from the anal verge. The MSK cohort comprised 1069 patients; of those, 710 were assigned to the model training group and 359 were assigned to the internal validation group. The SCC cohort comprised 331 patients; of those, 200 were assigned to the chemoradiotherapy group and 131 were assigned to the total neoadjuvant therapy with short-course radiotherapy group. The concordance indices in the MSK validation data set were 0.70 (95% CI, 0.65-0.76) for RFS and 0.73 (95% CI, 0.65-0.80) for OS. In the external SCC data set, the concordance indices in the chemoradiotherapy group were 0.71 (95% CI, 0.62-0.81) for RFS and 0.72 (95% CI, 0.59-0.85) for OS; the concordance indices in the total neoadjuvant therapy with short-course radiotherapy group were 0.62 (95% CI, 0.49-0.75) for RFS and 0.67 (95% CI, 0.46-0.84) for OS. Calibration plots confirmed good agreement between predicted and observed events. These results compared favorably with predictions based on the AJCC staging system (concordance indices for MSK validation: RFS = 0.69 [95% CI, 0.64-0.74]; OS = 0.67 [95% CI, 0.58-0.75]) and the NAR score (concordance indices for MSK validation: RFS = 0.56 [95% CI, 0.50-0.63]; OS = 0.56 [95% CI, 0.46-0.66]). Furthermore, the clinical calculators provided more individualized outcome estimates compared with the categorical schemas (eg, estimated RFS for patients with AJCC stage IIIB disease ranged from 7% to 68%). CONCLUSIONS AND RELEVANCE: In this prognostic study, clinical calculators were developed and validated; these calculators provided more individualized estimates of the likelihood of RFS and OS than the AJCC staging system or the NAR score among patients with rectal cancer who received multimodal treatment. The calculators were easy to use and applicable to both short- and long-course radiotherapy regimens, and they may be used to inform surveillance strategies and facilitate future clinical trials and statistical power calculations.