Surgical review highlights risk stratification and functional outcomes of LARS, suggesting AI may enhance care strategies.
Background and Aims: Low Anterior Resection Syndrome (LARS) is a debilitating sequela of sphincter-preserving rectal cancer surgery, manifesting as faecal urgency, incontinence, frequency and clustering. Despite oncologic success, LARS significantly compromises postoperative quality of life (QoL), with major LARS affecting up to 56% of patients. Over the past decade, a paradigm shift has occurred in its assessment, prediction, and management. Objectives: To synthesise global evidence from 2015 to 2025 on: (a) Pathophysiological mechanisms and risk predictors of LARS, (b) recent advances in conservative and interventional management, (c) integration of artificial intelligence (AI) for functional prediction and (d) regional disparities in care delivery and outcomes. Methods: A narrative review was conducted per SANRA guidelines. Literature was retrieved from PubMed, Embase, and Cochrane databases. Eligible studies included randomised controlled trials (RCTs), systematic reviews and meta-analyses addressing LARS outcomes, therapies, QoL impact, predictive models and implementation challenges. Results: Recent RCTs such as POLARiS and SANLARS have demonstrated the efficacy of transanal irrigation and sacral neuromodulation in reducing major LARS symptoms and improving QoL ( P < .001). Machine learning models (e.g., XGBoost) now outperform traditional predictive tools like the POLARS score (AUROC 0.89 vs. 0.82). However, significant gaps persist in access to diagnostic tools, specialist care and advanced therapies in low- and middle-income regions. Conclusions: LARS requires a multimodal, tiered management strategy informed by predictive analytics and guided by structured QoL assessments. Bridging regional gaps through decentralised care models, culturally contextualised guidelines and AI-integrated prognostication represents the next frontier in functional rectal cancer survivorship.
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Kumar et al. (2025) studied this question.
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