Dataset Information

Machine Learning Models to Predict Survival Outcomes According to the Surgical Approach of Primary Radical Hysterectomy in Patients with Early Cervical Cancer.

ABSTRACT: We purposed to develop machine learning models predicting survival outcomes according to the surgical approach for radical hysterectomy (RH) in early cervical cancer. In total, 1056 patients with 2009 FIGO stage IB cervical cancer who underwent primary type C RH by either open or laparoscopic surgery were included in this multicenter retrospective study. The whole dataset consisting of patients' clinicopathologic data was split into training and test sets with a 4:1 ratio. Using the training set, we developed models predicting the probability of 5-year progression-free survival (PFS) and overall survival (OS) with tenfold cross validation. The developed models were validated in the test set. In terms of predictive performance, we measured the area under the receiver operating characteristic curve (AUC) values. The logistic regression models comprised of preoperative variables yielded AUCs of 0.679 and 0.715 for predicting 5-year PFS and OS rates, respectively. Combining both logistic regression and multiple machine learning models, we constructed hybrid ensemble models, and these models showed much improved predictive performance, with 0.741 and 0.759 AUCs for predicting 5-year PFS and OS rates, respectively. We successfully developed models predicting disease recurrence and mortality after primary RH in patients with early cervical cancer. As the predicted value is calculated based on the preoperative factors, such as the surgical approach, these ensemble models would be useful for making decisions when choosing between open or laparoscopic RH.

SUBMITTER: Kim SI

PROVIDER: S-EPMC8345043 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

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Machine Learning Models to Predict Survival Outcomes According to the Surgical Approach of Primary Radical Hysterectomy in Patients with Early Cervical Cancer.

Kim Se Ik SI Lee Sungyoung S Choi Chel Hun CH Lee Maria M Suh Dong Hoon DH Kim Hee Seung HS Kim Kidong K Chung Hyun Hoon HH No Jae Hong JH Kim Jae-Weon JW Park Noh Hyun NH Song Yong-Sang YS Kim Yong Beom YB

Cancers 20210723 15

We purposed to develop machine learning models predicting survival outcomes according to the surgical approach for radical hysterectomy (RH) in early cervical cancer. In total, 1056 patients with 2009 FIGO stage IB cervical cancer who underwent primary type C RH by either open or laparoscopic surgery were included in this multicenter retrospective study. The whole dataset consisting of patients' clinicopathologic data was split into training and test sets with a 4:1 ratio. Using the training set ...[more]

PMID: 34359610

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Project description:ObjectiveTo examine the association between surgical volume and survival of women with early-stage cervical cancer who underwent radical hysterectomy.MethodsThis is a nationwide multicenter retrospective study examining consecutive women with clinical stage IB1-IIB cervical cancer who underwent radical hysterectomy and pelvic lymphadenectomy from 2004 to 2008 (N=5,964). The surgical volume per site over the 5-year period was defined as low-volume (fewer than 32 surgeries, 46 [39.7%] institutions, n=649 [10.9%]), mid-volume (32-104 surgeries, 60 [51.7%] institutions, n=3,662 [61.4%]), and high-volume (105 surgeries or more, 10 [8.6%] institutions, n=1,653 [27.7%]). Surgical volume-specific survival was examined with multivariable analysis and propensity score matching.ResultsThe median number of surgeries per site was 44 (interquartile range, 17-65). The 5-year disease-free survival rates among stage IB1-IIB disease were 77.2%, 79.9%, and 84.5% for low-, mid-, and high-volume groups, respectively. On multivariable analysis, women in high-volume centers had a decreased risk of recurrence (adjusted hazard ratio [HR] 0.69, 95% CI 0.58-0.82, P<.001) and all-cause mortality (adjusted HR 0.73, 95% CI 0.59-0.90, P=.003) compared with those in mid-volume centers. Specifically, women in high-volume centers had a decreased risk of local recurrence (adjusted HR 0.62, 95% CI 0.49-0.78, P<.001) but not distant recurrence (adjusted HR 0.85, 95% CI 0.67-1.06, P=.142) compared with those in mid-volume centers. Among 1,700 women with clinical stage IB1 disease treated with surgery alone, surgery at high-volume centers was associated with a decreased risk of recurrence (adjusted HR 0.45, 95% CI 0.25-0.79, P=.006) and all-cause mortality (adjusted HR 0.29, 95% CI 0.11-0.76, P=.013) compared with surgery at mid-volume centers on multivariable analysis. After propensity score matching, surgery at high-volume centers remained an independent prognostic factor for decreased recurrence (adjusted HR 0.69, 95% CI 0.57-0.84, P<.001) and all-cause mortality (adjusted HR 0.75, 95% CI 0.59-0.95, P=.016) compared with surgery at mid- and low-volume centers on multivariable analysis.ConclusionHospital volume for radical hysterectomy may be a prognostic factor for early-stage cervical cancer. Surgery at high-volume centers is associated with decreased local recurrence risk and improved survival.

Project description:ObjectiveTo evaluate the association of number of radical hysterectomies performed per year in each center with disease-free survival and overall survival.MethodsWe conducted an international, multicenter, retrospective study of patients previously included in the Surveillance in Cervical Cancer collaborative studies. Individuals with International Federation of Gynecology and Obstetrics (FIGO) 2009 stage IB1-IIA1 cervical cancer who underwent radical hysterectomy and had negative lymph nodes at final histology were included. Patients were treated at referral centers for gynecologic oncology according to updated national and international guidelines. Optimal cutoffs for surgical volume were identified using an unadjusted Cox proportional hazard model, with disease-free survival as the outcome and defined as the value that minimizes the P-value of the split in groups in terms of disease-free survival. Propensity score matching was used to create statistically similar cohorts at baseline.ResultsA total of 2,157 patients were initially included. The two most significant cutoffs for surgical volume were identified at seven and 17 surgical procedures, dividing the entire cohort into low-volume, middle-volume, and high-volume centers. After propensity score matching, 1,238 patients were analyzed-619 (50.0%) in the high-volume group, 523 (42.2%) in the middle-volume group, and 96 (7.8%) in the low-volume group. Patients who underwent surgery in higher-volume institutions had progressively better 5-year disease-free survival than those who underwent surgery in lower-volume centers (92.3% vs 88.9% vs 83.8%, P=.029). No difference was noted in 5-year overall survival (95.9% vs 97.2% vs 95.2%, P=.70). Cox multivariable regression analysis showed that FIGO stage greater than IB1, presence of lymphovascular space invasion, grade greater than 1, tumor diameter greater than 20 mm, minimally invasive surgical approach, nonsquamous cell carcinoma histology, and lower-volume centers represented independent risk factors for recurrence.ConclusionSurgical volume of centers represented an independent prognostic factor affecting disease-free survival. Increasing number of radical hysterectomies performed in each center every year was associated with improved disease-free survival.

Project description:BackgroundMinimally invasive surgery was adopted as an alternative to laparotomy (open surgery) for radical hysterectomy in patients with early-stage cervical cancer before high-quality evidence regarding its effect on survival was available. We sought to determine the effect of minimally invasive surgery on all-cause mortality among women undergoing radical hysterectomy for cervical cancer.MethodsWe performed a cohort study involving women who underwent radical hysterectomy for stage IA2 or IB1 cervical cancer during the 2010-2013 period at Commission on Cancer-accredited hospitals in the United States. The study used inverse probability of treatment propensity-score weighting. We also conducted an interrupted time-series analysis involving women who underwent radical hysterectomy for cervical cancer during the 2000-2010 period, using the Surveillance, Epidemiology, and End Results program database.ResultsIn the primary analysis, 1225 of 2461 women (49.8%) underwent minimally invasive surgery. Women treated with minimally invasive surgery were more often white, privately insured, and from ZIP Codes with higher socioeconomic status, had smaller, lower-grade tumors, and were more likely to have received a diagnosis later in the study period than women who underwent open surgery. Over a median follow-up of 45 months, the 4-year mortality was 9.1% among women who underwent minimally invasive surgery and 5.3% among those who underwent open surgery (hazard ratio, 1.65; 95% confidence interval [CI], 1.22 to 2.22; P=0.002 by the log-rank test). Before the adoption of minimally invasive radical hysterectomy (i.e., in the 2000-2006 period), the 4-year relative survival rate among women who underwent radical hysterectomy for cervical cancer remained stable (annual percentage change, 0.3%; 95% CI, -0.1 to 0.6). The adoption of minimally invasive surgery coincided with a decline in the 4-year relative survival rate of 0.8% (95% CI, 0.3 to 1.4) per year after 2006 (P=0.01 for change of trend).ConclusionsIn an epidemiologic study, minimally invasive radical hysterectomy was associated with shorter overall survival than open surgery among women with stage IA2 or IB1 cervical carcinoma. (Funded by the National Cancer Institute and others.).

Project description:ObjectiveCervical cancer (CC) continues to be a global burden for women, with higher incidence and mortality rates reported annually. Many countries have witnessed a dramatic reduction in the prevalence of CC due to widely accessed robotic radical hysterectomy (RRH). This network meta-analysis aims to compare intraoperative and postoperative outcomes in way of RRH, laparoscopic radical hysterectomy (LTH) and open radical hysterectomy (ORH) in the treatment of early-stage CC.MethodsA comprehensive search of PubMed, Cochrane Library and EMBASE databases was performed from inception to June 2016. Clinical controlled trials (CCTs) of above three hysterectomies in the treatment of early-stage CC were included in this study. Direct and indirect evidence were incorporated for calculating values of weighted mean difference (WMD) or odds ratio (OR), and drawing the surface under the cumulative ranking curve (SUCRA).ResultsSeventeen 17 CCTs were ultimately enrolled in this network meta-analysis. The network meta-analysis showed that patients treated by RRH and LRH had lower estimated blood loss compared to patients treated by ORH (WMD = -399.52, 95% CI = -600.64~-204.78; WMD = -277.86, 95%CI = -430.84 ~ -126.07, respectively). Patients treated by RRH and LRH had less hospital stay (days) than those by ORH (WMD = -3.49, 95% CI = -5.79~-1.24; WMD = -3.26, 95% CI = -5.04~-1.44, respectively). Compared with ORH, patients treated with RRH had lower postoperative complications (OR = 0.21, 95%CI = 0.08~0.65). Furthermore, the SUCRA value of three radical hysterectomies showed that patients receiving RRH illustrated better conditions on intraoperative blood loss, operation time, the number of resected lymph nodes, length of hospital stay and intraoperative and postoperative complications, while patients receiving ORH demonstrated relatively poorer conditions.ConclusionThe results of this meta-analysis confirmed that early-stage CC patients treated by RRH were superior to patients treated by LRH and ORH in intraoperative blood loss, length of hospital stay and intraoperative and postoperative complications, and RRH might be regarded as a safe and effective therapeutic procedure for the management of CC.

Project description:Background: The comparison of survival outcomes between minimally invasive surgery and open surgery for cervical cancer patients remains controversial. We evaluated the survival outcomes of cervical cancer patients who underwent different surgical approaches. Methods: A literature search was performed in PubMed, Embase, and Cochrane databases up to February 2020, using the MESH terms "minimally invasive surgical procedures" and "Uterine Cervical Neoplasms." Included were all original comparative studies and trials both published and unpublished in English that were related to minimally invasive surgery and open surgery for cervical cancer patients with International Federation of Gynecology and Obstetrics (FIGO) 2009 stage < IIB. Begg's and Egger's regressions were used to evaluate publication bias. Results: This meta-analysis included 28 studies enrolling 18,961 patients with cervical cancer. The overall analyses indicated that cervical cancer patients with FIGO 2009 stage < IIB who underwent minimally invasive surgery had a lower rate of OS (HR = 1.43, 95% CI = 1.06-1.92, P = 0.019) and DFS (HR = 1.50, 95% CI = 1.21-1.85, P < 0.001) than those who underwent open surgery. Moreover, minimally invasive surgery could lower OS (HR = 2.30, 95% CI = 1.50-3.52, P < 0.001) and DFS (HR = 1.94, 95% CI = 1.36-2.76, P < 0.001) of cervical cancer patients with FIGO 2009 stage ≤ IB1 compared to open surgery. However, there were no significant differences in OS (HR = 1.07, 95% CI = 0.65-1.76, P = 0.801) and DFS (HR = 1.20, 95% CI = 0.65-2.19, P = 0.559) in patients with tumors < 2 cm between the two groups. Conclusions: Minimally invasive radical hysterectomy was associated with poor survival outcomes compared to open surgery. Patients with FIGO 2009 stage ≤ IB1 cervical cancer who underwent minimally invasive surgery have lower OS and DFS rates than those who underwent open surgery. Therefore, open surgery should be performed for cervical cancer patients. However, patients with tumors < 2 cm might take the most advantage of minimally invasive surgery without increasing poor prognosis. There are some limitations in the meta-analysis, which needs further high-quality multicenter studies to confirm and update our findings.

Dataset Information

Machine Learning Models to Predict Survival Outcomes According to the Surgical Approach of Primary Radical Hysterectomy in Patients with Early Cervical Cancer.

Publications

Machine Learning Models to Predict Survival Outcomes According to the Surgical Approach of Primary Radical Hysterectomy in Patients with Early Cervical Cancer.

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