Abstract 183P
Background
Quality assurance is crucial for oncological surgical treatment assessment. For rare diseases, single-quality indicators are not enough. To develop a comprehensive and reproducible measurement, called the "Textbook Outcome” (TO), to assess the quality of surgical and prognosis of gastric neuroendocrine carcinoma (G-NEC) patients.
Methods
Data from patients with primary diagnosed gastric neuroendocrine neoplasms (G-NEN) included in the Study Group for Gastric Neuroendocrine Tumors (involving 24 high-volume Chinese hospitals, October 2005-September 2018) were analyzed. After applying the exclusion criteria, 860 G-NEC patients were included in this study. TO included receiving a curative resection, ≥15 lymph nodes (LNs) examined, no severe postoperative complication, hospital stay ≤21 days, and no hospital readmission ≤30 days after discharge. A Sankey plot displayed changes between TO and long-term survival. Hospital variation in TO was analyzed using a case mix-adjusted funnel plot. Prognostic factors for survival and risk factors for non-TO were analyzed using Cox and logistic regression analyses, respectively.
Results
TO was achieved in 56.6% of G-NEC patients. TO patients had better overall (OS), disease-free (DFS), and recurrence-free (RFS) survivals than non-TO patients (P <0.05). Sankey plot showed that the prognostic outcome of most TO patients flowed to alive (62.1%). Moreover, TO patients accounted for 60.3% of patients without recurrence. Multivariate Cox analysis revealed non-TO as an independent risk factor for OS, DFS, and RFS of G-NEC patients (P <0.05). Increasing TO rates were associated with improved OS for G-NEC patients, but not hospital volume. Multivariate logistic regression revealed that non-lower tumors, open surgery, and >200 ml blood loss were independent risk factors for non-TO patients (P <0.05).
Conclusions
TO is strongly associated with multicenter surgical quality and prognosis for G-NEC patients. Factors predicting non-TO are identified, which may help guide strategies to optimize G-NEC outcomes.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Scientific and Technological Innovation Joint Capital Projects of Fujian Province.
Disclosure
All authors have declared no conflicts of interest.
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