Analysis of risk factors for patients with early-stage cervical cancer: A study of 374 patients

Initial treatment for FIGO 2018 stage IIIC cervical cancer based on histological type: A 14-year multicenter study

BACKGROUND

To compare the oncological outcomes of radical chemotherapy (R-CT), abdominal radical hysterectomy (ARH), and neoadjuvant chemotherapy and radical surgery (NACT) for International Federation of Gynecology and Obstetrics (FIGO) 2018 stage IIIC cervical cancer, according to histological types: squamous cell carcinoma (SCC) and adenocarcinoma (AC)/adenosquamous cell carcinoma (ASC).

METHODS

A comparison of 5-year overall survival (OS) and disease-free survival (DFS) was performed for the SCC and AC/ASC subgroups for the three initial treatments, assessed using Kaplan-Meier and Cox proportional hazards regression analysis and validated using propensity score matching (PSM).

RESULTS

The study included 4086 patients: R-CT, n = 1913; ARH, n = 1529; and NACT, n = 644. AC/ASC had a lower survival rate (63.7%) than SCC (73.6%) and a higher recurrence and mortality rate (36.3% and 26.4%, respectively). The 5-year OS and DFS rates were different in the SCC group for R-CT, ARH, and NACT (OS: 69.8% vs. 80.8% vs. 73.0%, p < 0.001; DFS: 66.7% vs. 70.7% vs. 56.4%, p < 0.001), also in the AC/ASC group (OS: 46.1% vs. 70.6% vs. 55.6%, p < 0.001; DFS: 42.7% vs. 64.6% vs. 40.8%, p < 0.001). As for initial treatment, survival outcomes were worse for AC/ASC treated with R-CT and ARH than for SCC (both p < 0.05), with no group differences between the two treated with NACT.

CONCLUSION

Initial treatment influences oncological prognosis for patients with FIGO 2018 stage IIIC cervical cancer. ARH is an alternative treatment for stage IIIC cervical SCC and AC/ASC, and NACT needs to be chosen with caution, moreover, R-CT for AC/ASC requires careful selection.

Machine learning to reveal an astute risk predictive framework for Gynecologic Cancer and its impact on women psychology: Bangladeshi perspective

BACKGROUND

In this research, an astute system has been developed by using machine learning and data mining approach to predict the risk level of cervical and ovarian cancer in association to stress.

RESULTS

For functioning factors and subfactors, several machine learning models like Logistics Regression, Random Forest, AdaBoost, Naïve Bayes, Neural Network, kNN, CN2 rule Inducer, Decision Tree, Quadratic Classifier were compared with standard metrics e.g., F1, AUC, CA. For certainty info gain, gain ratio, gini index were revealed for both cervical and ovarian cancer. Attributes were ranked using different feature selection evaluators. Then the most significant analysis was made with the significant factors. Factors like children, age of first intercourse, age of husband, Pap test, age are the most significant factors of cervical cancer. On the other hand, genital area infection, pregnancy problems, use of drugs, abortion, and the number of children are important factors of ovarian cancer.

CONCLUSION

Resulting factors were merged, categorized, weighted according to their significance level. The categorized factors were indexed using ranker algorithm which provides them a weightage value. An algorithm has been formulated afterward which can be used to predict the risk level of cervical and ovarian cancer in relation to women's mental health. The research will have a great impact on the low incoming country like Bangladesh as most women in low incoming nations were unaware of it. As these two can be described as the most sensitive cancers to women, the development of the application from algorithm will also help to reduce women's mental stress. More data and parameters will be added in future for research in this perspective.

Neo-adjuvant chemotherapy in fertility-sparing cervical cancer treatment

The current review provides a literature overview of studies assessing the oncological and fertility outcomes of treatment with neo-adjuvant chemotherapy followed by fertility-sparing surgery in patients with cervical cancer >2 cm. Six cohort studies were included showing severe heterogeneity regarding patient selection, chemotherapy regimen, and surgical approach. In total, 111 patients were studied, with overall favorable characteristics. Patients were on average 29 years old, had a tumor of 36 mm, no lymph node metastasis, and response to chemotherapy. In approximately 5-year follow-up, the recurrence rate was 13% (0%-21%) and overall death rate 2.7% (0%-10%). Three patients were alive with recurrent disease (2.7% and 0%-11%). Of the 111 patients, 90 underwent successful fertility-sparing treatment (83%). Roughly one-third conceived and one-fourth had a healthy live-born child. More research is essential to determine proper selection criteria for fertility-sparing treatment of cervical cancer >2 cm and the optimal treatment management.