Background/Objectives: In real-world gastric cancer cohorts, incomplete TNM staging and heterogeneous biomarker testing may result from structural characteristics of diagnostic pathways rather than random data loss. This study aimed to evaluate staging completeness and tumour marker availability as pathway-linked phenomena and to examine their associations with metastatic presentation and treatment allocation at diagnosis. Methods: This retrospective observational study included consecutive patients with histologically confirmed gastric carcinoma or adenocarcinoma diagnosed between 2018 and 2021 at a tertiary referral centre. Incomplete staging was defined a priori as the presence of Tx and/or Nx and/or Mx. The primary analytic endpoint was incomplete staging within the subset of patients with defined M status. Secondary analyses evaluated the availability of both CEA and CA19-9. Univariable associations were assessed using Pearson’s χ2, and multivariable logistic regression models estimated adjusted odds ratios (ORs) with 95% confidence intervals (CIs). Predefined pathway-oriented endpoints were analysed using multivariable logistic regression models adjusted for key clinical and diagnostic variables. Results: Among 375 patients, incomplete staging occurred frequently and was strongly associated with metastatic disease (M1) and non-surgical management. In multivariable analysis, metastatic presentation remained independently associated with incomplete staging, whereas surgical management and explicit documentation of disease extension were inversely associated. Concurrent availability of CEA and CA19-9 was concentrated within non-surgical and metastatic pathways and was independently associated with documented disease extension. These findings suggest that both staging completeness and tumour marker testing are determined by pathway-specific structures rather than random processes. Conclusions: In real-world gastric cancer care, incomplete TNM staging and tumour marker availability function as measurable features of diagnostic architecture rather than random data limitations. By modelling documentation completeness and testing availability as pathway-dependent phenomena, this study provides a pragmatic framework for improving transparency and interpretability in observational oncology research.
Vieru et al. (2026) studied this question.
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