Survival outcomes after isolated local recurrence of rectal cancer and risk analysis affecting its resectability

Experience in the Application of Augmented Reality Technology in the Surgical Treatment of Patients Suffering Primary and Recurrent Pelvic Tumors

Surgical treatment of locally spread tumors in pelvic organs remains an urgent and complicated oncological problem. The recurrence rate after radical treatment ranges from 15.1% to 45.2%. The key to successful and safe surgical intervention lies in meticulous planning and intraoperative navigation, including the utilization of augmented reality (AR) technology. This paper presents the experience of clinically testing an AR technology application algorithm in the surgical treatment of 11 patients. The main stages of the algorithm are described. Radical operations incorporating intraoperative AR technology with favorable outcomes were performed on eight patients. One patient underwent a palliative intervention, while two patients did not undergo surgery. The testing of the algorithm for the application of AR technology in the surgical treatment of primary and recurrent pelvic tumors demonstrated both a technical possibility and reproducibility of this algorithm and the AR technology itself in clinical practice.

Nomogram to predict disease recurrence in patients with locally advanced rectal cancer undergoing rectal surgery after neoadjuvant therapy: retrospective cohort study

INTRODUCTION

Prognostic models can be used for predicting survival outcomes and guiding patient management. TNM staging alone is insufficient for predicting recurrence after chemoradiotherapy (CRT) and surgery for locally advanced rectal cancer. This study aimed to develop a nomogram to better predict cancer recurrence after CRT followed by total mesorectal excision (TME) and tailor postoperative management and follow-up.

MATERIALS AND METHODS

Between 2002 and 2019, data were retrospectively collected on patients with rectal adenocarcinoma. Data on sex, age, carcinoembryonic antigen (CEA) level, tumour location, induction chemotherapy, adjuvant chemotherapy, tumour downsizing, perineural invasion, lymphovascular invasion, pathological stage, resection margins (R0 versus R1), and pelvic septic complications were analysed. The variables significantly associated with cancer recurrence were used to build a nomogram that was validated in both the training and validation cohorts. Model performance was evaluated by receiver operating characteristic curve and area under the curve (AUC) analyses.

RESULTS

After applying exclusion criteria, 634 patients with rectal adenocarcinoma were included in this study. Eight factors (CEA level, adjuvant chemotherapy, tumour downsizing, perineural invasion, lymphovascular invasion, pathological stage, resection margins (R0 versus R1), and pelvic septic complications) were identified as nomogram variables. Our nomogram showed good performance with an AUC of 0.74 and 0.75 in the training and validation cohorts respectively.

CONCLUSION

Our nomogram is a simple tool for predicting cancer recurrence in patients with locally advanced rectal cancer after neoadjuvant CRT followed by TME. It provides an individual risk prediction of recurrence to tailor surveillance.