Association Between Surgical Technical Skill and Long-term Survival for Colon Cancer

Brajcich, Brian C.; Stulberg, Jonah J.; Palis, Bryan E.; Chung, Jeanette W.; Huang, Reiping; Bilimoria, Karl Y.

doi:10.1001/jamaoncol.2020.5462

Cited by 44 publications

(26 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Radical resection was considered to be the only curative approach for CC patients (25). Many patients could obtain 5year survival rate range from 60 to 79%, revealing the prognostic heterogeneity associated with this disease (26). In regard to prognostic heterogeneity, recent study demonstrated that colon cancer side should be acknowledged as a criterion for prognosis (14).…”

Section: Discussionmentioning

confidence: 99%

Development and Validation of the Individualized Prognostic Nomograms in Patients With Right- and Left-Sided Colon Cancer

Luo

et al. 2021

Front. Oncol.

View full text Add to dashboard Cite

BackgroundThe overall survival (OS) of patients diagnosed with colon cancer (CC) varied greatly, so did the patients with the same tumor stage. We aimed to design a nomogram that is capable of predicting OS in resected left-sided colon cancers (LSCC) and right-sided colon cancers (RSCC), and thus to stratify patients into different risk groups, respectively.MethodsRecords from a retrospective cohort of 577 patients with complete information were used to construct the nomogram. Univariate and multivariate analyses screened risk factors associated with overall survival. The performance of the nomogram was evaluated with concordance index (c-index), calibration plots, and decision curve analyses for discrimination, accuracy, calibration ability, and clinical net benefits, respectively, which was further compared with the American Joint Committee on Cancer (AJCC) 8th tumor-node-metastasis (TNM) classification. Risk stratification based on nomogram scores was performed with recursive partitioning analysis.ResultsThe LSCC nomogram incorporated carbohydrate antigen 12-5 (CA12-5), age and log odds of positive lymph nodes (LODDS), and RSCC nomogram enrolled tumor stroma percentage (TSP), age and LODDS. Compared with the TNM classification, the LSCC and RSCC nomograms both had a statistically higher C-index (0.837, 95% CI: 0.827–0.846 and 0.780, 95% CI 0.773–0.787, respectively) and more clinical net benefits, respectively. Calibration plots revealed no deviations from reference lines. All results were reproducible in the validation cohort.ConclusionsAn original predictive nomogram was constructed and validated for OS in patients with CC after surgery, which had facilitated physicians to appraise the individual survival of postoperative patients accurately and to identify high-risk patients who were in need of more aggressive treatment and follow-up strategies.

show abstract

Section: Discussionmentioning

confidence: 99%

Development and Validation of the Individualized Prognostic Nomograms in Patients With Right- and Left-Sided Colon Cancer

Luo

et al. 2021

Front. Oncol.

View full text Add to dashboard Cite

show abstract

“…A growing body of evidence supports the quantitative analysis of surgical video. 22,[44][45][46][47] One fundamental discovery has been the detection of signals in surgical video that predict patient outcome: surgeons have heterogeneous skill resulting in heterogeneous outcomes. 14,44,45,48 Although low-skill surgeons are more likely to have adverse intraoperative events, video of these events has not been systematically studied.…”

Section: Socalnet Performance Compared To Expertsmentioning

confidence: 99%

Expert Surgeons and Deep Learning Models Can Predict the Outcome of Surgical Hemorrhage from One Minute of Video

Pangal

Kugener

Zhu

et al. 2022

Preprint

View full text Add to dashboard Cite

Background: Major vascular injury resulting in uncontrolled bleeding is a catastrophic and often fatal complication of minimally invasive surgery. At the outset of these events, surgeons do not know how much blood will be lost or whether they will successfully control the hemorrhage (achieve hemostasis). We evaluate the ability of a deep learning neural network (DNN) to predict hemostasis control ability using the first minute of surgical video and compare model performance with human experts viewing the same video. Methods: The publicly available SOCAL dataset contains 147 videos of attending and resident surgeons managing hemorrhage in a validated, high-fidelity cadaveric simulator. Videos are labeled with outcome and blood loss (mL). The first minute of 20 videos was shown to four, blinded, fellowship trained skull-base neurosurgery instructors, and to SOCALNet (a DNN trained on SOCAL videos). SOCALNet architecture included a convolutional network (ResNet) identifying spatial features and a recurrent network identifying temporal features (LSTM). Experts independently assessed surgeon skill, predicted outcome and blood loss (mL). Outcome and blood loss predictions were compared with SOCALNet. Results: Expert inter-rater reliability was 0.95. Experts correctly predicted 14/20 trials (Sensitivity: 82%, Specificity: 55%, Positive Predictive Value (PPV): 69%, Negative Predictive Value (NPV): 71%). SOCALNet correctly predicted 17/20 trials (Sensitivity 100%, Specificity 66%, PPV 79%, NPV 100%) and correctly identified all successful attempts. Expert predictions of the highest and lowest skill surgeons and expert predictions reported with maximum confidence were more accurate. Experts systematically underestimated blood loss (mean error -131 mL, RMSE 350 mL, R2 0.70) and fewer than half of expert predictions identified blood loss > 500mL (47.5%, 19/40). SOCALNet had superior performance (mean error -57 mL, RMSE 295mL, R2 0.74) and detected most episodes of blood loss > 500mL (80%, 8/10). In validation experiments, SOCALNet evaluation of a critical on-screen surgical maneuver and high/low-skill composite videos were concordant with expert evaluation. Conclusion: Using only the first minute of video, experts and SOCALNet can predict outcome and blood loss during surgical hemorrhage. Experts systematically underestimated blood loss, and SOCALNet had no false negatives. DNNs can provide accurate, meaningful assessments of surgical video. We call for the creation of datasets of surgical adverse events for quality improvement research.

show abstract

“…La cirugía es la piedra angular del manejo del cáncer colorrectal (CCR) 1 , aunque se asocia con un alto riesgo de morbilidad y mortalidad. Las tasas de mortalidad general después de la cirugía colorrectal varían del 1 al 16,4 %, con tasas de morbilidad tan altas como el 40-50 % 2,3 , con las implicaciones desfavorables que ellas representan en términos de costos 4 , periodo libre de enfermedad y supervivencia global 5,6 .…”

Section: Introductionunclassified

Determinación de los factores predictivos para complicaciones en cirugía electiva de pacientes con cáncer colorrectal. Experiencia del Instituto de Cancerología Las Américas Auna (Colombia, 2016-2019)

et al. 2021

View full text Add to dashboard Cite

Introducción. El pilar fundamental del tratamiento del cáncer colorrectal es la cirugía, situación que expone a los pacientes a la posible presentación de complicaciones, morbimortalidad, pobre calidad de vida, recurrencia tumoral o la muerte. El objetivo de este estudio fue determinar las variables clínicas y quirúrgicas que inciden en el riesgo de la aparición de complicaciones en los pacientes con cáncer colorrectal llevados a cirugía electiva entre los años 2016 y 2019. Métodos. Estudio observacional, descriptivo, transversal y retrospectivo. Se incluyeron pacientes mayores de 18 años con cáncer colorrectal sometidos a cirugía electiva. Se realizó un análisis multivariado para determinar los factores que se relacionan con las complicaciones postquirúrgicas. Resultados. Se incluyeron 298 pacientes, 68 % mayores de 60 años, 52,3 % mujeres, 74,2 % presentaban comorbilidades y 48,3 % fueron diagnosticados en estadio III. El 48,3 % presentó complicaciones postoperatorias. De ellos, el 68,1 % no tenía tamización nutricional y el 61,8 % no tenía preparación del colon; un 55 % fueron cirugías del recto, 69,1 % de las cirugías fueron por vía laparoscópica y 71,8 % presentaron sangrado inferior a 500 ml. La mayoría de las complicaciones fueron clasificadas como Clavien-Dindo I-III. Discusión. Las características de los pacientes fueron similares a los presentados en otros estudios, aunque hubo mayor incidencia de íleo postoperatorio. El análisis multivariado mostró una mayor probabilidad de presentar una complicación en pacientes con diabetes mellitus, hipertensión arterial, falta de tamización nutricional o preparación de colon, cirugía de recto y el sangrado mayor a 500 ml.

show abstract

Association Between Surgical Technical Skill and Long-term Survival for Colon Cancer

Cited by 44 publications

References 5 publications

Development and Validation of the Individualized Prognostic Nomograms in Patients With Right- and Left-Sided Colon Cancer

Development and Validation of the Individualized Prognostic Nomograms in Patients With Right- and Left-Sided Colon Cancer

Expert Surgeons and Deep Learning Models Can Predict the Outcome of Surgical Hemorrhage from One Minute of Video

Determinación de los factores predictivos para complicaciones en cirugía electiva de pacientes con cáncer colorrectal. Experiencia del Instituto de Cancerología Las Américas Auna (Colombia, 2016-2019)

Contact Info

Product

Resources

About