ArticleAnnals of hepato-biliary-pancreatic surgery2020
Impact of lymph node staging systems in predicting outcome in patients with ampullary cancer.
Article in Annals of hepato-biliary-pancreatic surgery, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 7 citations in OpenAlex.
- Laparoscopic versus open pancreaticoduodenectomy: Long-term outcome from a tertiary care centre.Journal of minimal access surgery · 2024Article
- Developing and validating a prognostic nomogram for ovarian clear cell carcinoma patients: A retrospective comparison of lymph node staging schemes with competing risk analysis.Frontiers in oncology · 2022Article
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8 authors at 1 institution in 1 country.
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Abstract
BACKGROUNDS/
aimsLymph node (LN) metastasis though, is a poor prognostic factor for ampullary carcinoma (APC), the impact of Lymph node ratio (LNR) and Logarithm odds of positive lymph node (LODDS) in the long-term survival remains controversial. We evaluated the factors affecting the long-term outcome in APC patients with emphasis on LNR and LODDS.
methodsThe prospectively collected data of 198 patients who underwent pancreatoduodenectomy for APC was analyzed after excluding 12 patients for various reasons. Factors affecting Disease specific survival (DSS) and Recurrence free survival (RFS) were analyzed with special reference to LN positivity, LNR and LODDS.
resultsOut of 186, 117 (62.9%) patients were alive at a median follow-up of 39.5 months and 72 (38.7%) developed recurrence. The overall 5-year DSS was 59.3% & RFS 54.9%. Univariate analysis showed T-stage, tumor differentiation, perineural invasion, LN positivity, LNR and LODDS was significantly affected DSS and RFS. On multivariate analysis, perineural invasion, LN positivity, LNR and LODDS lost its significance for DSS and RFS. AUC for prediction of DSS and RFS for LNR was 0.654 (
conclusionsLNR and LODDS although independently seem to affect the RFS and DSS, albeit have a low sensitivity and specificity in predicting DSS and RFS.
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