The impact of adjuvant hysterectomy on survival outcomes of patients with locally advanced cervical cancer: A network meta-analysis

Adjuvant Hysterectomy in Patients After Radiation for Locally Advanced Cervical Cancer: A Single-Center Prospective Longitudinal Study

Introduction

Residual or recurrent cervical cancer post-CCRT is a challenging clinical issue, even though there has been much effort in recent decades to increase patient survival after radiation. There is a paucity of literature regarding the role of hysterectomy in recurrent/residual disease after radiation in LACC patients. Such a procedure is controversial and not routinely performed because of difficulties in obtaining tumor-free margins and the high rate of associated morbidity.

Aims and Objectives

Evaluate outcomes and morbidities in patients who had undergone hysterectomy for residual or recurrent disease after radiation in LACC patients.

Material and Methods

This is a prospective observational study on radiotherapy-treated LACC patients (IIB-III) with residual disease or recurrent disease who have undergone adjuvant hysterectomy. This study has been conducted at AHPGIC, Cuttack, with a sample size of 30 patients.

Results

18/30 patients underwent extrafascial hysterectomy, and rest 12 patients had radical hysterectomy. No significant difference in complications, achieving tumor free margins or recurrences post adjuvant hysterectomy based on the radicality of surgery was observed. 5 cases of recurrences post-adjuvant hysterectomy were detected. Some of the factors which had significant association with recurrences post adjuvant hysterectomy were non squamous histology, no preoperative brachytherapy, deep stromal invasion and positive surgical margins. Median follow-up time was 14 months (12-27 months).

Conclusion

This study shows that adjuvant hysterectomy is feasible with good outcome and acceptable morbidity after chemoradiotherapy in cervical cancer patients "If selection of patients for adjuvant hysterectomy is appropriate."

Controversies and Advances in the Personalized Surgical Treatment of Cervical Cancer

Cervical cancer represents a global health issue as it is mostly encountered in women of reproductive age, while at the same time, survival outcomes seem to have remained constant during the last two decades. The need to implement fertility-sparing strategies as well as to decrease the morbidity that accompanies radical treatment has been extensively studied. During the last decade, several randomized clinical trials have been released, resulting in significant advances in the surgical treatment of early-stage disease. At the same time, evidence about the surgical treatment of advanced-stage disease as well as recurrent disease has gradually appeared and seems to be promising, thus leading the point forward towards personalized medicine that will remove the surgical barriers that seem concrete in our era. Nevertheless, the discrepancies in perioperative morbidity and survival outcomes that were observed among published studies raise several questions. In the present article, we chose to review the gray fields in the surgical treatment of early-stage and advanced-stage cervical cancer. Studies that are based on strong evidence that support current clinical practice are compared to smaller cohorts that present novel data that may form the basis for future research, and issues that remain poorly explored are discussed in an effort to help establish a consensus for future research development.

CAM-VT: A Weakly supervised cervical cancer nest image identification approach using conjugated attention mechanism and visual transformer

Cervical cancer is the fourth most common cancer among women, and cytopathological images are often used to screen for this cancer. However, manual examination is very troublesome and the misdiagnosis rate is high. In addition, cervical cancer nest cells are denser and more complex, with high overlap and opacity, increasing the difficulty of identification. The appearance of the computer aided automatic diagnosis system solves this problem. In this paper, a weakly supervised cervical cancer nest image identification approach using Conjugated Attention Mechanism and Visual Transformer (CAM-VT), which can analyze pap slides quickly and accurately. CAM-VT proposes conjugated attention mechanism and visual transformer modules for local and global feature extraction respectively, and then designs an ensemble learning module to further improve the identification capability. In order to determine a reasonable interpretation, comparative experiments are conducted on our datasets. The average accuracy of the validation set of three repeated experiments using CAM-VT framework is 88.92%, which is higher than the optimal result of 22 well-known deep learning models. Moreover, we conduct ablation experiments and extended experiments on Hematoxylin and Eosin stained gastric histopathological image datasets to verify the ability and generalization ability of the framework. Finally, the top 5 and top 10 positive probability values of cervical nests are 97.36% and 96.84%, which have important clinical and practical significance. The experimental results show that the proposed CAM-VT framework has excellent performance in potential cervical cancer nest image identification tasks for practical clinical work.

Current Resources for Evidence-Based Practice, May 2022

An extensive review of new resources to support the provision of evidence-based care for women and infants. The current column includes a discussion of the roles of researchers and clinicians in fostering evidence-based practice, diagnostic test accuracy in suspected preeclampsia, and the effectiveness of decision-making tools in patients with pre-pregnancy morbidities.