Disparities in Outcomes following Resection of Locally Advanced Rectal Cancer.

Surgical margins following rectal cancer resection impact oncologic outcomes. We examined the relationship between margin status and race, ethnicity, region of care, and facility type. Patients undergoing resection of a stage II-III locally advanced rectal cancer (LARC) between 2004 and 2018 were identified through the National Cancer Database. Inverse probability of treatment weighting (IPTW) was performed, with margin positivity rate as the outcome of interest, and race/ethnicity and region of care as the predictors of interest. In total, 58,389 patients were included. After IPTW adjustment, non-Hispanic Black (NHB) patients were 12% (p = 0.029) more likely to have margin positivity than non-Hispanic White (NHW) patients. Patients in the northeast were 9% less likely to have margin positivity compared to those in the south. In the west, NHB patients were more likely to have positive margins than NHW patients. Care in academic/research centers was associated with lower likelihood of positive margins compared to community centers. Within academic/research centers, NHB patients were more likely to have positive margins than non-Hispanic Other patients. Our results suggest that disparity in surgical management of LARC in NHB patients exists across regions of the country and facility types. Further research aimed at identifying drivers of this disparity is warranted.

Watch and Wait for Near-Complete Responders-A Word of Caution.

This Viewpoint discusses the establishment of a cutoff point as the watch and wait approach is increasingly used in patients with locally advanced rectal cancer.

Factors Associated With Performing IPAA After Total Colectomy for Ulcerative Colitis.

BACKGROUND: IPAA is considered the procedure of choice for restorative surgery after total colectomy for ulcerative colitis. Previous studies have examined the rate of IPAA within individual states but not at the national level in the United States. OBJECTIVE: This study aimed to assess the rate of IPAA after total colectomy for ulcerative colitis in a national population and identify factors associated with IPAA. DESIGN: This was a retrospective cohort study. SETTINGS: This study was performed in the United States. PATIENTS: Patients who were aged 18 years or older and who underwent total colectomy between 2009 and 2019 for a diagnosis of ulcerative colitis were identified within a commercial database. This database excluded patients with public insurance, including all patients older than 65 years with Medicare. MAIN OUTCOME MEASURES: The primary outcome was IPAA. Multivariable logistic regression was used to assess the association between covariates and the likelihood of undergoing IPAA. RESULTS: In total, 2816 patients were included, of whom 1414 (50.2%) underwent IPAA, 928 (33.0%) underwent no further surgery, and 474 (16.8%) underwent proctectomy with end ileostomy. Younger age, lower comorbidities, elective case, and laparoscopic approach in the initial colectomy were significantly associated with IPAA but socioeconomic status was not. LIMITATIONS: This retrospective study included only patients with commercial insurance. CONCLUSIONS: A total of 50.2% of patients who had total colectomy for ulcerative colitis underwent IPAA, and younger age, lower comorbidities, and elective cases are associated with a higher rate of IPAA placement. This study emphasizes the importance of ensuring follow-up with colorectal surgeons to provide the option of restorative surgery, especially for patients undergoing urgent or emergent colectomies. See Video Abstract . FACTORES ASOCIADOS CON LA REALIZACIN DE ANASTOMOSIS ANALBOLSA ILEAL DESPUS DE UNA COLECTOMA TOTAL POR COLITIS ULCEROSA: ANTECEDENTES:La anastomosis ileo-anal se considera el procedimiento de elección para la cirugía reparadora tras la colectomía total por colitis ulcerosa. Estudios previos han examinado la tasa de anastomosis ileo-anal dentro de los estados individuales, pero no a nivel nacional en los Estados Unidos.OBJETIVO:Evaluar la tasa de anastomosis bolsa ileal-anal después de la colectomía total para la colitis ulcerosa en una población nacional e identificar los factores asociados con la anastomosis bolsa ileal-anal.DISEÑO:Se trata de un estudio de cohortes retrospectivo.LUGAR:Este estudio se realizó en los Estados Unidos.PACIENTES:Los pacientes que tenían ≥18 años de edad que se sometieron a colectomía total entre 2009 y 2019 para un diagnóstico de colitis ulcerosa fueron identificados dentro de una base de datos comercial. Esta base de datos excluyó a los pacientes con seguro público, incluidos todos los pacientes >65 años con Medicare.MEDIDAS DE RESULTADO PRINCIPALES:El resultado primario fue la anastomosis ileal bolsa-anal. Se utilizó una regresión logística multivariable para evaluar la asociación entre las covariables y la probabilidad de someterse a una anastomosis ileal.RESULTADOS:En total, se incluyeron 2.816 pacientes, de los cuales 1.414 (50,2%) se sometieron a anastomosis ileo-anal, 928 (33,0%) no se sometieron a ninguna otra intervención quirúrgica y 474 (16,8%) se sometieron a proctectomía con ileostomía terminal. La edad más joven, las comorbilidades más bajas, el caso electivo, y el abordaje laparoscópico en la colectomía inicial se asociaron significativamente con la anastomosis ileal bolsa-anal, pero no el estatus socioeconómico.LIMITACIONES:Este estudio retrospectivo incluyó sólo pacientes con seguro comercial.CONCLUSIONES:Un 50,2% de los pacientes se someten a anastomosis ileo-anal y la edad más joven, las comorbilidades más bajas y los casos electivos se asocian con una mayor tasa de colocación de anastomosis ileo-anal. Esto subraya la importancia de asegurar el seguimiento con cirujanos colorrectales para ofrecer la opción de cirugía reparadora, especialmente en pacientes sometidos a colectomías urgentes o emergentes. (Traducción-Dr. Yolanda Colorado ).

Long-Term Results of Organ Preservation in Patients With Rectal Adenocarcinoma Treated With Total Neoadjuvant Therapy: The Randomized Phase II OPRA Trial.

Clinical trials frequently include multiple end points that mature at different times. The initial report, typically based on the primary end point, may be published when key planned co-primary or secondary analyses are not yet available. Clinical Trial Updates provide an opportunity to disseminate additional results from studies, published in JCO or elsewhere, for which the primary end point has already been reported.To assess long-term risk of local tumor regrowth, we report updated organ preservation rate and oncologic outcomes of the OPRA trial (ClinicalTrials.gov identifier: NCT02008656). Patients with stage II/III rectal cancer were randomly assigned to receive induction chemotherapy followed by chemoradiation (INCT-CRT) or chemoradiation followed by consolidation chemotherapy (CRT-CNCT). Patients who achieved a complete or near-complete response after finishing treatment were offered watch-and-wait (WW). Total mesorectal excision (TME) was recommended for those who achieved an incomplete response. The primary end point was disease-free survival (DFS). The secondary end point was TME-free survival. In total, 324 patients were randomly assigned (INCT-CRT, n = 158; CRT-CNCT, n = 166). Median follow-up was 5.1 years. The 5-year DFS rates were 71% (95% CI, 64 to 79) and 69% (95% CI, 62 to 77) for INCT-CRT and CRT-CNCT, respectively (P = .68). TME-free survival was 39% (95% CI, 32 to 48) in the INCT-CRT group and 54% (95% CI, 46 to 62) in the CRT-CNCT group (P = .012). Of 81 patients with regrowth, 94% occurred within 2 years and 99% occurred within 3 years. DFS was similar for patients who underwent TME after restaging (64% [95% CI, 53 to 78]) and patients in WW who underwent TME after regrowth (64% [95% CI, 53 to 78]; P = .94). Updated analysis continues to show long-term organ preservation in half of the patients with rectal cancer treated with total neoadjuvant therapy. In patients who enter WW, most cases of tumor regrowth occur in the first 2 years.

Prediction of Pathologic Complete Response for Rectal Cancer Based on Pretreatment Factors Using Machine Learning.

BACKGROUND: Pathologic complete response after neoadjuvant therapy is an important prognostic indicator for locally advanced rectal cancer and may give insights into which patients might be treated nonoperatively in the future. Existing models for predicting pathologic complete response in the pretreatment setting are limited by small data sets and low accuracy. OBJECTIVE: We sought to use machine learning to develop a more generalizable predictive model for pathologic complete response for locally advanced rectal cancer. DESIGN: Patients with locally advanced rectal cancer who underwent neoadjuvant therapy followed by surgical resection were identified in the National Cancer Database from years 2010 to 2019 and were split into training, validation, and test sets. Machine learning techniques included random forest, gradient boosting, and artificial neural network. A logistic regression model was also created. Model performance was assessed using an area under the receiver operating characteristic curve. SETTINGS: This study used a national, multicenter data set. PATIENTS: Patients with locally advanced rectal cancer who underwent neoadjuvant therapy and proctectomy. MAIN OUTCOME MEASURES: Pathologic complete response defined as T0/xN0/x. RESULTS: The data set included 53,684 patients. Pathologic complete response was experienced by 22.9% of patients. Gradient boosting showed the best performance with an area under the receiver operating characteristic curve of 0.777 (95% CI, 0.773-0.781), compared with 0.684 (95% CI, 0.68-0.688) for logistic regression. The strongest predictors of pathologic complete response were no lymphovascular invasion, no perineural invasion, lower CEA, smaller size of tumor, and microsatellite stability. A concise model including the top 5 variables showed preserved performance. LIMITATIONS: The models were not externally validated. CONCLUSIONS: Machine learning techniques can be used to accurately predict pathologic complete response for locally advanced rectal cancer in the pretreatment setting. After fine-tuning a data set including patients treated nonoperatively, these models could help clinicians identify the appropriate candidates for a watch-and-wait strategy. See Video Abstract . EL CNCER DE RECTO BASADA EN FACTORES PREVIOS AL TRATAMIENTO MEDIANTE EL APRENDIZAJE AUTOMTICO: ANTECEDENTES:La respuesta patológica completa después de la terapia neoadyuvante es un indicador pronóstico importante para el cáncer de recto localmente avanzado y puede dar información sobre qué pacientes podrían ser tratados de forma no quirúrgica en el futuro. Los modelos existentes para predecir la respuesta patológica completa en el entorno previo al tratamiento están limitados por conjuntos de datos pequeños y baja precisión.OBJETIVO:Intentamos utilizar el aprendizaje automático para desarrollar un modelo predictivo más generalizable para la respuesta patológica completa para el cáncer de recto localmente avanzado.DISEÑO:Los pacientes con cáncer de recto localmente avanzado que se sometieron a terapia neoadyuvante seguida de resección quirúrgica se identificaron en la Base de Datos Nacional del Cáncer de los años 2010 a 2019 y se dividieron en conjuntos de capacitación, validación y prueba. Las técnicas de aprendizaje automático incluyeron bosque aleatorio, aumento de gradiente y red neuronal artificial. También se creó un modelo de regresión logística. El rendimiento del modelo se evaluó utilizando el área bajo la curva característica operativa del receptor.ÁMBITO:Este estudio utilizó un conjunto de datos nacional multicéntrico.PACIENTES:Pacientes con cáncer de recto localmente avanzado sometidos a terapia neoadyuvante y proctectomía.PRINCIPALES MEDIDAS DE VALORACIÓN:Respuesta patológica completa definida como T0/xN0/x.RESULTADOS:El conjunto de datos incluyó 53.684 pacientes. El 22,9% de los pacientes experimentaron una respuesta patológica completa. El refuerzo de gradiente mostró el mejor rendimiento con un área bajo la curva característica operativa del receptor de 0,777 (IC del 95%: 0,773 - 0,781), en comparación con 0,684 (IC del 95%: 0,68 - 0,688) para la regresión logística. Los predictores más fuertes de respuesta patológica completa fueron la ausencia de invasión linfovascular, la ausencia de invasión perineural, un CEA más bajo, un tamaño más pequeño del tumor y la estabilidad de los microsatélites. Un modelo conciso que incluye las cinco variables principales mostró un rendimiento preservado.LIMITACIONES:Los modelos no fueron validados externamente.CONCLUSIONES:Las técnicas de aprendizaje automático se pueden utilizar para predecir con precisión la respuesta patológica completa para el cáncer de recto localmente avanzado en el entorno previo al tratamiento. Después de realizar ajustes en un conjunto de datos que incluye pacientes tratados de forma no quirúrgica, estos modelos podrían ayudar a los médicos a identificar a los candidatos adecuados para una estrategia de observar y esperar. (Traducción-Dr. Ingrid Melo ).

Exploring Stakeholders' Perspectives on Implementing Universal Germline Testing for Colorectal Cancer: Findings From a Clinical Practice Survey.

PURPOSE: New guidelines recommend considering germline genetic testing for all patients with colorectal cancer (CRC). However, there is a lack of data on stakeholders' perspectives on the advantages and barriers of implementing universal germline testing (UGT). This study assessed the perspectives of members of the Collaborative Group of the Americas on Inherited Gastrointestinal Cancer (CGA-IGC) regarding the implementation of UGT for patients with CRC, including readiness, logistics, and barriers. METHODS: A cross-sectional survey was sent to 317 active members of CGA-IGC. The survey included sections on demographics, clinical practice specialty, established institutional practices for testing, and questions pertaining to support of and barriers to implementing UGT for patients with CRC. RESULTS: Eighty CGA-IGC members (25%) participated, including 42 genetic counselors (53%) and 14 gastroenterologists (18%). Forty-seven (59%) reported an academic medical center as their primary work setting, and most participants (56%) had more than 10 years of clinical practice. Although most participants (73%) supported UGT, 54% indicated that changes in practice would be required before adopting UGT, and 39% indicated that these changes would be challenging to implement. There was support for both genetics and nongenetics providers to order genetic testing, and a majority (57%) supported a standardized multigene panel rather than a customized gene panel. Key barriers to UGT implementation included limited genetics knowledge among nongenetics providers, time-consuming processes for obtaining consent, ordering tests, disclosing results, and lack of insurance coverage. CONCLUSION: This study demonstrates wide support among hereditary GI cancer experts for implementation of UGT for patients with CRC. However, alternative service delivery models using nongenetics providers should be considered to address the logistical barriers to UGT implementation, particularly the growing demand for genetic testing.

"Free-Floating Anus": A Flap-Free Approach for Definitive Excision of Circumferential Giant Condyloma Acuminata.

Giant condyloma acuminata (GCA), or Buschke-Löwenstein tumor, is a rare exophytic cauliflower-like growth in the anogenital region. The spectrum of treatment options is wide, ranging from the application of topical ointments to the performance of an abdominoperineal resection. Currently, wide local excision is the most common approach and may entail the creation of a protective loop ileostomy or implementation of flaps or grafts that facilitate closure. We describe a unique surgical approach for the management of circumferential GCA void of the use a protective loop ileostomy, flaps, or grafts. Our report highlights that the implementation of a radical, circumferential, wide excision resulting in "free-floating anus" and healing via secondary intention can ultimately lead to excellent functional and cosmetic results and therefore may be considered a minimally invasive surgical option for patients afflicted with a large, circumferential GCA.

Estimating Risk of Locoregional Failure and Overall Survival in Anal Cancer Following Chemoradiation: A Machine Learning Approach.

BACKGROUND: Optimal treatment of anal squamous cell carcinoma (ASCC) is definitive chemoradiation. Patients with persistent or recurrent disease require abdominoperineal resection (APR). Current models for predicting need for APR and overall survival are limited by low accuracy or small datasets. This study sought to use machine learning (ML) to develop more accurate models for locoregional failure and overall survival for ASCC. METHODS: This study used the National Cancer Database from 2004-2018, divided into training, validation, and test sets. We included patients with stage I-III ASCC who underwent chemoradiation. Our primary outcomes were need for APR and 3-year overall survival. Random forest (RF), gradient boosting (XGB), and neural network (NN) ML-based models were developed and compared with logistic regression (LR). Accuracy was assessed using area under the receiver operating characteristic curve (AUROC). RESULTS: APR was required in 5.3% (1,015/18,978) of patients. XGB performed best with AUROC of 0.813, compared with 0.691 for LR. Tumor size, lymphovascular invasion, and tumor grade showed the strongest influence on model predictions. Mortality was 23.6% (7,988/33,834). AUROC for XGB and LR were similar at 0.766 and 0.748, respectively. For this model, age, radiation dose, sex, and insurance status were the most influential variables. CONCLUSIONS: We developed and internally validated machine learning-based models for predicting outcomes in ASCC and showed higher accuracy versus LR for locoregional failure, but not overall survival. After external validation, these models may assist clinicians with identifying patients with ASCC at high risk of treatment failure.

New Opportunities for Minimizing Toxicity in Rectal Cancer Management.

Advances in multimodal management of locally advanced rectal cancer (LARC), consisting of preoperative chemotherapy and/or radiotherapy followed by surgery with or without adjuvant chemotherapy, have improved local disease control and patient survival but are associated with significant risk for acute and long-term morbidity. Recently published trials, evaluating treatment dose intensification via the addition of preoperative induction or consolidation chemotherapy (total neoadjuvant therapy [TNT]), have demonstrated improved tumor response rates while maintaining acceptable toxicity. In addition, TNT has led to an increased number of patients achieving a clinical complete response and thus eligible to pursue a nonoperative, organ-preserving, watch and wait approach, thereby avoiding toxicities associated with surgery, such as bowel dysfunction and stoma-related complications. Ongoing trials using immune checkpoint inhibitors in patients with mismatch repair-deficient tumors suggest that this subgroup of patients with LARC could potentially be treated with immunotherapy alone, sparing them the toxicity associated with preoperative treatment and surgery. However, the majority of rectal cancers are mismatch repair-proficient and less responsive to immune checkpoint inhibitors and require multimodal management. The synergy noted in preclinical studies between immunotherapy and radiotherapy on immunogenic tumor cell death has led to the design of ongoing clinical trials that explore the benefit of combining radiotherapy, chemotherapy, and immunotherapy (mainly of immune checkpoint inhibitors) and aim to increase the number of patients eligible for organ preservation.

Current chemoprevention approaches in Lynch syndrome and Familial adenomatous polyposis: a global clinical practice survey.

Background: International chemoprevention preferences and approaches in Lynch syndrome (LS) and APC-associated polyposis, including Familial adenomatous polyposis (FAP) and attenuated FAP (AFAP) have not been previously explored. Aim: To describe current chemoprevention strategies for patients with LS or FAP/AFAP (referred to collectively as FAP) practiced by members of four international hereditary cancer societies through administration of a survey. Results: Ninety-six participants across four hereditary gastrointestinal cancer societies responded to the survey. Most respondents (91%, 87/96) completed information regarding their demographics and practice characteristics relating to hereditary gastrointestinal cancer and chemoprevention clinical practices. Sixty-nine percent (60/87) of respondents offer chemoprevention for FAP and/or LS as a part of their practice. Of the 75% (72/96) of survey respondents who were eligible to answer practice-based clinical vignettes based off of their responses to ten barrier questions regarding chemoprevention, 88% (63/72) of those participants completed at least one case vignette question to further characterize chemoprevention practices in FAP and/or LS. In FAP, 51% (32/63) would offer chemoprevention for rectal polyposis, with sulindac - 300 mg (18%, 10/56) and aspirin (16%, 9/56) being the most frequently selected options. In LS, 93% (55/59) of professionals discuss chemoprevention and 59% (35/59) frequently recommend chemoprevention. Close to half of the respondents (47%, 26/55) would recommend beginning aspirin at time of commencement of the patient's first screening colonoscopy (usually at age 25yrs). Ninety-four percent (47/50) of respondents would consider a patient's diagnosis of LS as an influential factor for aspirin use. There was no consensus on the dose of aspirin (≤100 mg, >100 mg - 325 mg or 600 mg) to offer patients with LS and there was no agreement on how other factors, such as BMI, hypertension, family history of colorectal cancer, and family history of heart disease, would affect the recommendation for aspirin use. Possible harm among older patients (>70 years) was identified as the most common reason to discourage aspirin use. Conclusion: Although chemoprevention is widely discussed and offered to patients with FAP and LS by an international group of hereditary gastrointestinal cancer experts, there is significant heterogeneity in how it is applied in clinical practice.

Prediction of Ureteral Injury During Colorectal Surgery Using Machine Learning.

BACKGROUND: Ureteral injury (UI) is a rare but devastating complication during colorectal surgery. Ureteral stents may reduce UI but carry risks themselves. Risk predictors for UI could help target the use of stents, but previous efforts have relied on logistic regression (LR), shown moderate accuracy, and used intraoperative variables. We sought to use an emerging approach in predictive analytics, machine learning, to create a model for UI. METHODS: Patients who underwent colorectal surgery were identified in the National Surgical Quality Improvement Program (NSQIP) database. Patients were split into training, validation, and test sets. The primary outcome was UI. Three machine learning approaches were tested including random forest (RF), gradient boosting (XGB), and neural networks (NN), and compared with traditional LR. Model performance was assessed using area under the curve (AUROC). RESULTS: The data set included 262,923 patients, of whom 1519 (.578%) experienced UI. Of the modeling techniques, XGB performed the best, with an AUROC score of .774 (95% CI .742-.807) compared with .698 (95% CI .664-.733) for LR. Random forest and NN performed similarly with scores of .738 and .763, respectively. Type of procedure, work RVUs, indication for surgery, and mechanical bowel prep showed the strongest influence on model predictions. CONCLUSIONS: Machine learning-based models significantly outperformed LR and previous models and showed high accuracy in predicting UI during colorectal surgery. With proper validation, they could be used to support decision making regarding the placement of ureteral stents preoperatively.

Delphi Initiative for Early-Onset Colorectal Cancer (DIRECt) International Management Guidelines.

BACKGROUND & AIMS: Patients with early-onset colorectal cancer (eoCRC) are managed according to guidelines that are not age-specific. A multidisciplinary international group (DIRECt), composed of 69 experts, was convened to develop the first evidence-based consensus recommendations for eoCRC. METHODS: After reviewing the published literature, a Delphi methodology was used to draft and respond to clinically relevant questions. Each statement underwent 3 rounds of voting and reached a consensus level of agreement of ≥80%. RESULTS: The DIRECt group produced 31 statements in 7 areas of interest: diagnosis, risk factors, genetics, pathology-oncology, endoscopy, therapy, and supportive care. There was strong consensus that all individuals younger than 50 should undergo CRC risk stratification and prompt symptom assessment. All newly diagnosed eoCRC patients should receive germline genetic testing, ideally before surgery. On the basis of current evidence, endoscopic, surgical, and oncologic treatment of eoCRC should not differ from later-onset CRC, except for individuals with pathogenic or likely pathogenic germline variants. The evidence on chemotherapy is not sufficient to recommend changes to established therapeutic protocols. Fertility preservation and sexual health are important to address in eoCRC survivors. The DIRECt group highlighted areas with knowledge gaps that should be prioritized in future research efforts, including age at first screening for the general population, use of fecal immunochemical tests, chemotherapy, endoscopic therapy, and post-treatment surveillance for eoCRC patients. CONCLUSIONS: The DIRECt group produced the first consensus recommendations on eoCRC. All statements should be considered together with the accompanying comments and literature reviews. We highlighted areas where research should be prioritized. These guidelines represent a useful tool for clinicians caring for patients with eoCRC.

Improved Prediction of Surgical-Site Infection After Colorectal Surgery Using Machine Learning.

BACKGROUND: Surgical-site infection is a source of significant morbidity after colorectal surgery. Previous efforts to develop models that predict surgical-site infection have had limited accuracy. Machine learning has shown promise in predicting postoperative outcomes by identifying nonlinear patterns within large data sets. OBJECTIVE: This study aimed to seek usage of machine learning to develop a more accurate predictive model for colorectal surgical-site infections. DESIGN: Patients who underwent colorectal surgery were identified in the American College of Surgeons National Quality Improvement Program database from years 2012 to 2019 and were split into training, validation, and test sets. Machine-learning techniques included random forest, gradient boosting, and artificial neural network. A logistic regression model was also created. Model performance was assessed using area under the receiver operating characteristic curve. SETTINGS: A national, multicenter data set. PATIENTS: Patients who underwent colorectal surgery. MAIN OUTCOME MEASURES: The primary outcome (surgical-site infection) included patients who experienced superficial, deep, or organ-space surgical-site infections. RESULTS: The data set included 275,152 patients after the application of exclusion criteria. Of all patients, 10.7% experienced a surgical-site infection. Artificial neural network showed the best performance with area under the receiver operating characteristic curve of 0.769 (95% CI, 0.762-0.777), compared with 0.766 (95% CI, 0.759-0.774) for gradient boosting, 0.764 (95% CI, 0.756-0.772) for random forest, and 0.677 (95% CI, 0.669-0.685) for logistic regression. For the artificial neural network model, the strongest predictors of surgical-site infection were organ-space surgical-site infection present at time of surgery, operative time, oral antibiotic bowel preparation, and surgical approach. LIMITATIONS: Local institutional validation was not performed. CONCLUSIONS: Machine-learning techniques predict colorectal surgical-site infections with higher accuracy than logistic regression. These techniques may be used to identify patients at increased risk and to target preventive interventions for surgical-site infection. See Video Abstract at http://links.lww.com/DCR/C88 . PREDICCIN MEJORADA DE LA INFECCIN DEL SITIO QUIRRGICO DESPUS DE LA CIRUGA COLORRECTAL MEDIANTE EL APRENDIZAJE AUTOMTICO: ANTECEDENTES:La infección del sitio quirúrgico es una fuente de morbilidad significativa después de la cirugía colorrectal. Los esfuerzos anteriores para desarrollar modelos que predijeran la infección del sitio quirúrgico han tenido una precisión limitada. El aprendizaje automático se ha mostrado prometedor en la predicción de los resultados posoperatorios mediante la identificación de patrones no lineales dentro de grandes conjuntos de datos.OBJETIVO:Intentamos utilizar el aprendizaje automático para desarrollar un modelo predictivo más preciso para las infecciones del sitio quirúrgico colorrectal.DISEÑO:Los pacientes que se sometieron a cirugía colorrectal se identificaron en la base de datos del Programa Nacional de Mejoramiento de la Calidad del Colegio Estadounidense de Cirujanos de los años 2012 a 2019 y se dividieron en conjuntos de capacitación, validación y prueba. Las técnicas de aprendizaje automático incluyeron conjunto aleatorio, aumento de gradiente y red neuronal artificial. También se creó un modelo de regresión logística. El rendimiento del modelo se evaluó utilizando el área bajo la curva característica operativa del receptor.CONFIGURACIÓN:Un conjunto de datos multicéntrico nacional.PACIENTES:Pacientes intervenidos de cirugía colorrectal.PRINCIPALES MEDIDAS DE RESULTADO:El resultado primario (infección del sitio quirúrgico) incluyó pacientes que experimentaron infecciones superficiales, profundas o del espacio de órganos del sitio quirúrgico.RESULTADOS:El conjunto de datos incluyó 275.152 pacientes después de la aplicación de los criterios de exclusión. El 10,7% de los pacientes presentó infección del sitio quirúrgico. La red neuronal artificial mostró el mejor rendimiento con el área bajo la curva característica operativa del receptor de 0,769 (IC del 95 %: 0,762 - 0,777), en comparación con 0,766 (IC del 95 %: 0,759 - 0,774) para el aumento de gradiente, 0,764 (IC del 95 %: 0,756 - 0,772) para conjunto aleatorio y 0,677 (IC 95% 0,669 - 0,685) para regresión logística. Para el modelo de red neuronal artificial, los predictores más fuertes de infección del sitio quirúrgico fueron la infección del sitio quirúrgico del espacio del órgano presente en el momento de la cirugía, el tiempo operatorio, la preparación intestinal con antibióticos orales y el abordaje quirúrgico.LIMITACIONES:No se realizó validación institucional local.CONCLUSIONES:Las técnicas de aprendizaje automático predicen infecciones del sitio quirúrgico colorrectal con mayor precisión que la regresión logística. Estas técnicas se pueden usar para identificar a los pacientes con mayor riesgo y para orientar las intervenciones preventivas para la infección del sitio quirúrgico. Consulte Video Resumen en http://links.lww.com/DCR/C88 . (Traducción-Dr Yolanda Colorado ).

Quality of life and function after rectal cancer surgery with and without sphincter preservation.

Despite improvements in surgical techniques, functional outcomes and quality of life after therapy for rectal cancer remain suboptimal. We sought to prospectively evaluate the effect of bowel, bladder, and sexual functional outcomes on health-related quality of life (QOL) in patients with restorative versus non-restorative resections after rectal cancer surgery. A cohort of 211 patients with clinical stage I-III rectal cancer who underwent open surgery between 2006 and 2009 at Memorial Sloan Kettering were included. Subjects were asked to complete surveys preoperatively and at 6, 12, and 24 months after surgery. Validated instruments were used to measure QOL, bowel, bladder, and sexual function. Univariable and multivariable regression analyses evaluated predictors of 24- month QOL. In addition, longitudinal trends over the study period were evaluated using repeated measures models. In total, 180 patients (85%) completed at least 1 survey, and response rates at each time point were high (>70%). QOL was most impaired at 6 and 12 months and returned to baseline levels at 24 months. Among patients who underwent sphincter-preserving surgery (SPS; n=153 [85%]), overall bowel function at 24 months was significantly impaired and never returned to baseline. There were no differences in QOL at 24 months between patients who underwent SPS and those who did not (p=.29). Bowel function was correlated with QOL at 24 months (Pearson correlation,.41; p<.001). QOL among patients who have undergone SPS for rectal cancer is good despite poor function. Patients with ostomies are able to adjust to the functional changes and, overall, have good global QOL. Patients with low anastomoses had lower global QOL at 24 months than patients with permanent stomas. Our findings can help patients set expectations about function and quality of life after surgery for rectal cancer with and without a permanent stoma.

Development and Validation of Machine Learning Models to Predict Readmission After Colorectal Surgery.

BACKGROUND: Readmission after colorectal surgery is common and often implies complications for patients and costs for hospitals. Previous works have created predictive models using logistic regression for this outcome but have shown limited accuracy. Machine learning has shown promise in improving predictions by identifying non-linear patterns in data. We sought to create a more accurate predictive model for readmission after colorectal surgery using machine learning. METHODS: Patients who underwent colorectal surgery were identified in the National Quality Improvement Program (NSQIP) database including years 2012-2019 and split into training, validation, and test sets. The primary outcome was readmission within 30 days of surgery. Three types of machine learning models were created, including random forest (RF), gradient boosting (XGB), and neural network (NN). A logistic regression (LR) model was also created for comparison. Model performance was evaluated using area under the receiver operating characteristic curve (AUROC). RESULTS: The dataset included 213,827 patients after application of exclusion criteria. A total of 23,083 (10.8%) of patients experienced readmission. NN obtained an AUROC of 0.751 (95% CI 0.743-0.759), compared with 0.684 (95% CI 0.676-0.693) for LR. RF and XGB performed similarly with AUROCs of 0.749 (95% CI 0.741-0.757) and 0.745 (95% CI 0.737-0.753) respectively. Ileus, index admission length of stay, organ-space surgical site infection present at time of surgery, and ostomy placement were identified as the most contributory variables. CONCLUSIONS: Machine learning approaches outperformed traditional statistical methods in the prediction of readmission after colorectal surgery. After external validation, this improved prediction model could be used to target interventions to reduce readmission rate.

Predictors of operative difficulty in robotic low anterior resection for rectal cancer.

AIM: This study evaluates the relationship of tumour and anatomical features with operative difficulty in robotic low anterior resection performed by four experienced surgeons in a high-volume colorectal cancer practice. METHODS: Data from 382 patients who underwent robotic low anterior resection by four expert surgeons between January 2016 and June 2019 were included in the analysis. Operating time was used as a measure of operative difficulty. Univariate and multivariate mixed models were used to identify associations between baseline characteristics and operating time, with surgeon as a random effect, thereby controlling for variability in surgeon speed and proficiency. In an exploratory analysis, operative difficulty was defined as conversion to laparotomy, a positive margin or an incomplete mesorectum. RESULTS: Median operating time was 4.28 h (range 1.95-11.33 h) but varied by surgeon from 3.45 h (1.95-6.10 h) to 5.93 h (3.33-11.33 h) (P < 0.001). Predictors of longer operating time in multivariate analysis were male sex, higher body mass index, neoadjuvant radiotherapy, low tumour height, greater sacral height and larger mesorectal area at the S5 vertebral level. Conversion occurred in two cases (0.5%), and incomplete mesorectum and positive margins were found in nine (2.4%) and 19 (5.0%) patients, respectively. Neoadjuvant radiotherapy and larger pelvic outlet were the only characteristics associated with the exploratory measure of difficulty. CONCLUSION: Predicting operative difficulty based on easy to identify, preoperative radiological and clinical variables is feasible in robotic anterior resection.

Differential Performance of Machine Learning Models in Prediction of Procedure-Specific Outcomes.

BACKGROUND: Procedure-specific complications can have devastating consequences. Machine learning-based tools have the potential to outperform traditional statistical modeling in predicting their risk and guiding decision-making. We sought to develop and compare deep neural network (NN) models, a type of machine learning, to logistic regression (LR) for predicting anastomotic leak after colectomy, bile leak after hepatectomy, and pancreatic fistula after pancreaticoduodenectomy (PD). METHODS: The colectomy, hepatectomy, and PD National Surgical Quality Improvement Program (NSQIP) databases were analyzed. Each dataset was split into training, validation, and testing sets in a 60/20/20 ratio, with fivefold cross-validation. Models were created using NN and LR for each outcome. Models were evaluated primarily with area under the receiver operating characteristic curve (AUROC). RESULTS: A total of 197,488 patients were included for colectomy, 25,403 for hepatectomy, and 23,333 for PD. For anastomotic leak, AUROC for NN was 0.676 (95% 0.666-0.687), compared with 0.633 (95% CI 0.620-0.647) for LR. For bile leak, AUROC for NN was 0.750 (95% CI 0.739-0.761), compared with 0.722 (95% CI 0.698-0.746) for LR. For pancreatic fistula, AUROC for NN was 0.746 (95% CI 0.733-0.760), compared with 0.713 (95% CI 0.703-0.723) for LR. Variables related to intra-operative information, such as surgical approach, biliary reconstruction, and pancreatic gland texture were highly important for model predictions. DISCUSSION: Machine learning showed a marginal advantage over traditional statistical techniques in predicting procedure-specific outcomes. However, models that included intra-operative information performed better than those that did not, suggesting that NSQIP procedure-targeted datasets may be strengthened by including relevant intra-operative information.

Organ Preservation in Patients With Rectal Adenocarcinoma Treated With Total Neoadjuvant Therapy.

PURPOSE: Prospective data on the efficacy of a watch-and-wait strategy to achieve organ preservation in patients with locally advanced rectal cancer treated with total neoadjuvant therapy are limited. METHODS: In this prospective, randomized phase II trial, we assessed the outcomes of 324 patients with stage II or III rectal adenocarcinoma treated with induction chemotherapy followed by chemoradiotherapy (INCT-CRT) or chemoradiotherapy followed by consolidation chemotherapy (CRT-CNCT) and either total mesorectal excision (TME) or watch-and-wait on the basis of tumor response. Patients in both groups received 4 months of infusional fluorouracil-leucovorin-oxaliplatin or capecitabine-oxaliplatin and 5,000 to 5,600 cGy of radiation combined with either continuous infusion fluorouracil or capecitabine during radiotherapy. The trial was designed as two stand-alone studies with disease-free survival (DFS) as the primary end point for both groups, with a comparison to a null hypothesis on the basis of historical data. The secondary end point was TME-free survival. RESULTS: Median follow-up was 3 years. Three-year DFS was 76% (95% CI, 69 to 84) for the INCT-CRT group and 76% (95% CI, 69 to 83) for the CRT-CNCT group, in line with the 3-year DFS rate (75%) observed historically. Three-year TME-free survival was 41% (95% CI, 33 to 50) in the INCT-CRT group and 53% (95% CI, 45 to 62) in the CRT-CNCT group. No differences were found between groups in local recurrence-free survival, distant metastasis-free survival, or overall survival. Patients who underwent TME after restaging and patients who underwent TME after regrowth had similar DFS rates. CONCLUSION: Organ preservation is achievable in half of the patients with rectal cancer treated with total neoadjuvant therapy, without an apparent detriment in survival, compared with historical controls treated with chemoradiotherapy, TME, and postoperative chemotherapy.

Survival After Induction Chemotherapy and Chemoradiation Versus Chemoradiation and Adjuvant Chemotherapy for Locally Advanced Rectal Cancer.

BACKGROUND: Total neoadjuvant therapy (TNT) improves tumor response in locally advanced rectal cancer (LARC) patients compared to neoadjuvant chemoradiotherapy alone. The effect of TNT on patient survival has not been fully investigated. MATERIALS AND METHODS: This was a retrospective case series of patients with LARC at a comprehensive cancer center. Three hundred and eleven patients received chemoradiotherapy (chemoRT) as the sole neoadjuvant treatment and planned adjuvant chemotherapy, and 313 received TNT (induction fluorouracil and oxaliplatin-based chemotherapy followed by chemoradiotherapy in the neoadjuvant setting). These patients then underwent total mesorectal excision or were entered in a watch-and-wait protocol. The proportion of patients with complete response (CR) after neoadjuvant therapy (defined as pathological CR or clinical CR sustained for 2 years) was compared by the χ2 test. Disease-free survival (DFS), local recurrence-free survival, distant metastasis-free survival, and overall survival were assessed by Kaplan-Meier analysis and log-rank test. Cox regression models were used to further evaluate DFS. RESULTS: The rate of CR was 20% for chemoRT and 27% for TNT (P=.05). DFS, local recurrence-free survival, metastasis-free survival, and overall survival were no different. Disease-free survival was not associated with the type of neoadjuvant treatment (hazard ratio [HR] 1.3; 95% confidence interval [CI] 0.93-1.80; P = .12). CONCLUSIONS: Although TNT does not prolong survival than neoadjuvant chemoradiotherapy plus intended postoperative chemotherapy, the higher response rate associated with TNT may create opportunities to preserve the rectum in more patients with LARC.