This study develops the Surgical Assessment and Healthcare (SAH) Index, a new tool to fairly evaluate gastric cancer surgery outcomes. Gastric cancer is a serious disease that often requires major surgery, but it can be difficult to compare how well different hospitals or surgeons perform because patients have different levels of risk before surgery.

The SAH Index will help solve this problem by creating a standardized way to account for patient risk factors when evaluating surgical results. The study analyzes data from 780 patients who had gastric cancer surgery in 2019, looking at factors like patient age, tumor characteristics, molecular markers, and surgical outcomes.

By combining clinical information (like patient health), pathological details (like tumor type), and molecular features (like genetic markers), the SAH Index will create risk categories that allow fair comparison of surgical outcomes. This tool could help hospitals improve their care, help patients and families understand their treatment options, and help doctors make better treatment decisions.

The study uses only existing medical records and does not involve any new treatments or procedures. The goal is to create a practical tool that can be used by hospitals and doctors to better evaluate and improve gastric cancer surgery outcomes.

Gastric cancer remains a leading cause of cancer-related mortality worldwide, with significant variation in surgical outcomes across healthcare institutions. Current outcome reporting lacks adequate risk adjustment, making it difficult to distinguish between differences in patient populations versus actual care quality. This limitation hampers quality improvement efforts and evidence-based decision making.

This retrospective cohort study addresses this gap by developing the Surgical Assessment and Healthcare (SAH) Index, a comprehensive risk-adjustment tool specifically designed for gastric cancer surgery evaluation. The study leverages a unique dataset combining clinical, pathological, and molecular characteristics of 780 consecutive gastric cancer patients who underwent surgical resection in 2019.

The SAH Index development follows established risk prediction modeling methodology. Univariate analysis will identify potential predictors across four domains: clinical factors (demographics, comorbidities, performance status), surgical factors (procedure type, surgeon experience), pathological factors (tumor stage, grade, Lauren classification), and molecular factors (HER2, microsatellite instability, mismatch repair status, PD-L1 expression). Multivariable Cox regression and logistic regression models will be constructed for survival and morbidity outcomes, respectively.

Model development includes variable selection using backward elimination, assessment of multicollinearity, and evaluation of interaction terms. Internal validation will employ bootstrap resampling techniques to assess model stability and prevent overfitting. The final SAH Index will stratify patients into distinct risk categories with corresponding risk-adjusted outcome predictions.

Performance metrics include discrimination (C-statistic), calibration (Hosmer-Lemeshow test), and clinical utility assessment. The index will be validated against existing risk stratification tools and tested for its ability to detect outcome differences between healthcare providers after risk adjustment.

This study represents the first comprehensive attempt to create a gastric cancer-specific surgical risk index incorporating molecular biomarkers, addressing a critical need in surgical quality assessment and comparative effectiveness research.

Inclusion Criteria:

• Age: 18 years and older Diagnosis: Histologically confirmed gastric adenocarcinoma Treatment: Underwent surgical resection in 2019 Data availability: Complete clinical, pathological, and molecular marker data Follow-up: Minimum 6 months post-operative follow-up data available

Exclusion Criteria:

• Histology: Non-adenocarcinoma gastric tumors Surgery type: Emergency surgery or palliative procedures only Data quality: Missing essential clinical, pathological, or molecular data required for SAH Index development Follow-up: Lost to follow-up within 30 days post-surgery

Consecutive patients who underwent surgical resection for gastric adenocarcinoma in 2019. The cohort represents a real-world surgical population with complete clinical, pathological, and molecular characterization including TNM staging, Lauren classification, and biomarker status (HER2, MSI, MMR). Patients span all age groups, tumor stages, and surgical approaches, providing a representative sample for SAH Index development and validation. Long-term follow-up data available for survival and complication analysis.

This describes your 780-patient cohort while staying under character limits and highlighting the comprehensive nature of your dataset.

Individual patient data will not be shared to protect patient privacy and comply with institutional data governance policies. The study involves retrospective analysis of clinical records containing sensitive medical information. De-identified aggregate results and statistical findings will be published to contribute to scientific knowledge while maintaining patient confidentiality.