Machine learning based prediction of recurrence after curative resection for rectal cancer.

PURPOSE: Patients with rectal cancer without distant metastases are typically treated with radical surgery. Post curative resection, several factors can affect tumor recurrence. This study aimed to analyze factors related to rectal cancer recurrence after curative resection using different machine learning techniques. METHODS: Consecutive patients who underwent curative surgery for rectal cancer between 2004 and 2018 at Gil Medical Center were included. Patients with stage IV disease, colon cancer, anal cancer, other recurrent cancer, emergency surgery, or hereditary malignancies were excluded from the study. The Synthetic Minority Oversampling Technique with Tomek link (SMOTETomek) technique was used to compensate for data imbalance between recurrent and no-recurrent groups. Four machine learning methods, logistic regression (LR), support vector machine (SVM), random forest (RF), and Extreme gradient boosting (XGBoost), were used to identify significant factors. To overfit and improve the model performance, feature importance was calculated using the permutation importance technique. RESULTS: A total of 3320 patients were included in the study. After exclusion, the total sample size of the study was 961 patients. The median follow-up period was 60.8 months (range:1.2-192.4). The recurrence rate during follow-up was 13.2% (n = 127). After applying the SMOTETomek method, the number of patients in both groups, recurrent and non-recurrent group were equalized to 667 patients. After analyzing for 16 variables, the top eight ranked variables {pathologic Tumor stage (pT), sex, concurrent chemoradiotherapy, pathologic Node stage (pN), age, postoperative chemotherapy, pathologic Tumor-Node-Metastasis stage (pTNM), and perineural invasion} were selected based on the order of permutational importance. The highest area under the curve (AUC) was for the SVM method (0.831). The sensitivity, specificity, and accuracy were found to be 0.692, 0.814, and 0.798, respectively. The lowest AUC was obtained for the XGBoost method (0.804), with a sensitivity, specificity, and accuracy of 0.308, 0.928, and 0.845, respectively. The variable with highest importance was pT as assessed through SVM, RF, and XGBoost (0.06, 0.12, and 0.13, respectively), whereas pTNM had the highest importance when assessed by LR (0.05). CONCLUSIONS: In the current study, SVM showed the best AUC, and the most influential factor across all machine learning methods except LR was found to be pT. The rectal cancer patients who have a high pT stage during postoperative follow-up are need to be more close surveillance.

Comparison of Long-Term Oncologic Outcomes Between Surgical T4 and T3 in Patients Diagnosed With Pathologic Stage IIA Right Colon Cancer.

Purpose: T stage plays an important role in the classification of subgroups in stage II colon cancer. Patients with pathologic T4 are at high risk of recurrence and it is recommended to include adjuvant chemotherapy in the treatment plan, while this is not necessary in pathologic T3. There is a discrepancy between the surgical T stage (sT), as determined by the surgeon in the operative field, and pathologic T stage (pT). The pathologic stage is considered a standard prognostic factor, but it has not been established whether the surgical stage has an oncologic impact. The aim of this study was to compare oncologic outcomes between sT4 and sT3 in pathologic stage IIA right colon cancer. Methods: Between January 2005 and December 2018, there were 354 patients who underwent right hemicolectomy performed by a single surgeon (JHB) at a tertiary hospital. The data from these patients were retrospectively collected and analyzed. Only those patients with pathologic stage IIA (pT3N0M0) right colon adenocarcinomas were included in this study. Patients with mucinous carcinoma, signet ring cell carcinoma, squamous cell carcinoma, or hereditary colon cancer, and who had emergent surgery were excluded. Finally, 86 patients were included in this study. The patients were categorized, according to their surgical records, into either the sT4 group (n=28) or the sT3 group (n=58). Results: There were no statistical differences between the two groups in terms of age, sex, body mass index, comorbidities, cancer location, histologic grade, lymphovascular invasion, perineural invasion, number of harvested lymph nodes, and adjuvant chemotherapy. The 5-year overall survival rate was significantly different between the sT4 and sT3 groups (92.6% vs. 97.7%, p=0.024). In addition, the 5-year disease-free survival rate was significantly different between the sT4 and sT3 groups (88.6% vs. 97.7%, p=0.017). In the multivariate Cox regression analysis, a classification of sT4 was a significant independent predictive factor for recurrence (p = 0.023). Conclusions: Long-term oncologic outcomes have shown significant differences between surgical T4 and T3 in pathologic stage IIA right colon cancer patients. Further large-scale, multicenter studies are required to verify the clinical impact of the surgical staging.

The efficacy of oxidized regenerated cellulose (SurgiGuard®) in breast cancer patients who undergo total mastectomy with node surgery: A prospective randomized study in 94 patients.

BACKGROUND: Seromas frequently develop in patients who undergo total mastectomy with node surgery. We aimed to prospectively explore whether use of oxidized regenerated cellulose (ORC, SurgiGuard®) affects seroma formation after total mastectomy with node surgery (sentinel lymph node biopsy (SLNB) or axillary lymph node dissection (ALND)). MATERIALS AND METHODS: Ninety four breast cancer patients were enrolled in the study who underwent total mastectomy with ALND or SLNB. The patients were randomized into two groups, one treated with ORC plus closed suction drainage and the other with closed suction drainage alone. RESULTS: Mean drainage volume was slightly lower in the ORC group on postoperative day 1 (123 ± 54 vs 143 ± 104 ml), but was slightly higher at all other time points; however, these differences were not significant. Mean total drainage volume in patients treated with ORC plus drainage did not differ from that of patients treated with drainage alone (1134 ± 507 ml vs 1033 ± 643 ml, P = 0.486). CONCLUSIONS: Use of ORC (SurgiGuard®) did not significantly alter the risk of seroma formation.

Morphologic Study of Gastric Sleeves by CT Volumetry at One Year after Laparoscopic Sleeve Gastrectomy.

Purpose: Laparoscopic sleeve gastrectomy (SG) is now frequently performed as a definitive bariatric procedure. The aim of the study was to evaluate the detailed morphology of remnant stomachs after SG with respect to volume and sleeve migration. Materials and Methods: We performed a retrospective review of prospectively collected data on patients that completed a 12-month postop examination, which included CT volumetry of sleeve, and a questionnaire that addressed postop food tolerance. CT volumetry study included total sleeve volume (TSV), tube volume (TV), antral volume (AV), tube/antral volume ratio (TAVR), and the presence of intrathoracic sleeve migration (ITSM). Results: Fifty-five patients were included in this retrospective study. Mean %TWL (% total weight loss) at 12 months postop was 32.8% (14.3-55.5), and mean TSV, TV, AV, and TAVR were 166.6±63.3 ml, 68.9±35.4 ml, 97.7±42.9 ml, and 0.8±0.6 respectively. TSV was not correlated significantly with %TWL at 12 months postop (r=-0.069, P=0.619). Fourteen patients (14/55, 25.5%) showed ITSM by CT. Patients with ITSM had a significantly lower mean GER score (5.1±2.0 vs. 7.3±2.0, P=0.001), a lower total food tolerance score (21.6±3.8 vs. 24.4±4.6, P=0.048), and a higher proportion showed suboptimal weight loss (35.7% vs. 9.8%, P=0.023). Conclusion: Mean TSV was not found to be significantly correlated with %TWL at 12 months postop. Patients with suboptimal weight loss had higher mean TAVR, and the presence of ITSM indicated more frequent GER symptoms, lower food tolerance, and a higher probability of suboptimal weight loss.