Predicting surgical benefit of primary tumor resection in patients with stage IV colorectal cancer.

BACKGROUND: There exists continuous controversy regarding the benefit of primary tumor resection (PTR) for stage IV colorectal cancer (CRC) patients. Little is known about how to predict the patients' benefit from PTR. This study aimed to develop a tool for surgical benefit prediction. METHODS: Stage IV CRC patients diagnosed between 2010 and 2015 from the Surveillance, Epidemiology and End Results database were included. Patients receiving PTR who survived longer than the median cancer-specific survival (CSS) time of those who did not undergo PTR were considered to benefit from surgery. Logistic regression analysis identified prognostic factors influencing surgical benefit, based on which a nomogram was constructed. The data of patients who underwent PTR from our institution was used for external validation. A user-friendly webserver was then built for convenient clinical use. RESULTS: The median CSS of the PTR group was 23 months, significantly longer than that of the non-PTR group (7 months, P < 0.001). In the PTR group, 23.3% of patients did not benefit from surgery. Logistic regression analysis identified age, marital status, tumor location, CEA level, chemotherapy, metastasectomy, tumor size, tumor deposits, number of examined lymph nodes, N stage, histological grade and number of distant metastases as independently associated with surgical benefit. The established prognostic nomogram demonstrated satisfactory performance in both the internal and external validation. CONCLUSION: PTR was associated with prolonged CSS in stage IV CRC. The proposed nomogram could be used as an evidenced-based platform for risk-to-benefit assessment to select appropriate patients for undergoing PTR.

Pathological-Features-Modified TNM Staging System Improves Prognostic Accuracy for Rectal Cancer.

BACKGROUND: Variations in survival outcomes are observed in the eighth edition of the American Joint Committee on Cancer TNM staging system. OBJECTIVE: Machine learning ensemble methods were used to develop and evaluate the effectiveness of a pathological-features-modified TNM staging system in predicting survival for patients with rectal cancer by use of commonly reported pathological features, such as histological grade, tumor deposits, and perineural invasion, to improve the prognostic accuracy. DESIGN: This was a retrospective population-based study. SETTINGS: Data were assessed from the database of the Surveillance, Epidemiology, and End Results Program. PATIENTS: The study cohort comprised 14,468 patients with rectal cancer diagnosed between 2010 and 2015. The development cohort included those who underwent surgery as the primary treatment, whereas patients who received neoadjuvant therapy were assigned to the validation cohort. MAIN OUTCOME MEASURES: The primary outcome measures included cumulative rectal cancer survival, adjusted HRs, and both calibration and discrimination statistics to evaluate model performance and internal validation. RESULTS: Multivariable Cox regression analysis identified all 3 pathological features as prognostic factors, after which patients were categorized into 4 pathological groups based on the number of pathological features (ie, 0, 1, 2, and 3). Distinct survival differences were observed among the groups, especially with patients with stage III rectal cancer. The proposed pathological-features-modified TNM staging outperformed the TNM staging in both the development and validation cohorts. LIMITATIONS: Retrospective in design and lack of external validation. CONCLUSIONS: The proposed pathological-features-modified TNM staging could complement the current TNM staging by improving the accuracy of survival estimation of patients with rectal cancer. See Video Abstract . EL SISTEMA DE ESTADIFICACIN TNM CON CARACTERSTICAS PATOLGICAS MODIFICADO MEJORA LA PRECISIN DEL PRONSTICO DEL CNCER DE RECTO: ANTECEDENTES:Se observan variaciones en los resultados de supervivencia en el sistema de estadificación TNM del Comité Conjunto Americano del Cáncer 8º ediciónOBJETIVO:Se utilizaron métodos conjuntos de aprendizaje automático para desarrollar y evaluar la eficacia de un sistema de estadificación con características patológicas modificadas de tumores, ganglios y metástasis para predecir la supervivencia de pacientes con cáncer de recto, utilizando algunas características patológicas comúnmente informadas, como el grado histológico, depósitos tumorales e invasión perineural, para mejorar la precisión del pronóstico.DISEÑO:Este fue un estudio retrospectivo de base poblacional.ENTERNO CLINICO:Se recuperaron y evaluaron datos de la base de datos de Vigilancia, Epidemiología y Resultados Finales.PACIENTES:La cohorte del estudio estuvo compuesta por 14,468 pacientes con cáncer de recto diagnosticados entre 2010 y 2015. La cohorte de desarrollo incluyó a aquellos que se sometieron a cirugía como tratamiento primario, mientras que los pacientes que recibieron terapia neoadyuvante fueron asignados a la cohorte de validación.PRINCIPALES MEDIDAS DE RESULTADO:Las medidas de resultado primarias incluyeron supervivencia acumulada del cáncer de recto, índices de riesgo ajustados y estadísticas de calibración y discriminación para evaluar el rendimiento del modelo y la validación interna.RESULTADOS:El análisis de regresión multivariable de Cox identificó las tres características patológicas como factores pronósticos, después de lo cual los pacientes se clasificaron en cuatro grupos patológicos según el número de características patológicas (es decir, 0, 1, 2 y 3). Se observaron distintas diferencias en la supervivencia entre los grupos, especialmente en los pacientes en estadio III. La estadificación propuesta con características patológicas modificadas de tumores-ganglios-metástasis superó a la estadificación TNM tanto en las cohortes de desarrollo como en las de validación.LIMITACIONES:Diseño retrospectivo y falta de validación externa.CONCLUSIONES:La estadificación propuesta con características patológicas modificadas de tumores-ganglios-metástasis podría complementar la estadificación TNM actual al mejorar la precisión de la estimación de supervivencia de los pacientes con cáncer de recto. (Traducción- Dr. Francisco M. Abarca-Rendon ).

Which treatment strategy is optimal for acute left-sided malignant colonic obstruction? A Bayesian meta-analysis.

PURPOSE: This study aimed to determine the best treatment for acute left-sided malignant colonic obstruction (ALMCO) among emergency surgery (ES), self-expanding metallic stent (SEMS), transanal drainage tube (TD), and decompressive stoma (DS). METHOD: Articles that compared two or more treatments of ALMCO were searched from PubMed, Cochrane Library, and Embase. Network meta-analyses were performed to calculate the outcomes of primary anastomosis, stoma creation, morbidity, mortality, and 5-year survival. RESULTS: Fifty-one articles met inclusion criteria. TD was the optimal treatment in performing primary anastomosis [probability of ranking first (Pro-1) 0.96], while ES was the worst [probability of ranking fourth (Pro-4) 0.99]. More permanent stoma was formed in ES and TD groups than in SEMS and DS groups [OR (95%CI): TD vs SEMS: 4.12 (1.89, 9.45); TD vs DS: 3.39 (1.46, 8.75); ES vs DS: 2.55 (1.73, 4.17); SEMS vs ES: 0.33 (0.24, 0.42)]. More morbidity occurred in ES group than in SEMS group [OR (95%CI): ES vs SEMS: 1.44 (1.14, 1.82)]. Besides, SEMS was ranked first in avoiding infection (Pro-4 0.95). For in-hospital mortality, ES was ranked first (Pro-1 0.93). TD was ranked first in recurrence (Pro-1 0.97) and metastasis (Pro-1 0.98). There was no discrepancy in 5-year overall and disease-free survival among all strategies. CONCLUSION: SEMS as a bridge to surgery reduces stoma formation, and morbidity especially the infection rate with relatively great oncological outcomes. Therefore, SEMS should be recommended first for ALMCO in the medical center with experience and conditions.