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Validating an algorithm to identify metastatic gastric cancer in the absence of routinely collected TNM staging data.

ABSTRACT: BACKGROUND:Accurate TNM stage information is essential for cancer health services research, but is often impractical and expensive to collect at the population-level. We evaluated algorithms using administrative healthcare data to identify patients with metastatic gastric cancer. METHODS:A population-based cohort of gastric cancer patients diagnosed between 2005 and 2007 identified from the Ontario Cancer Registry were linked to routinely collected healthcare data. Reference standard data identifying metastatic disease were obtained from a province-wide chart review, according to the Collaborative Staging method. Algorithms to identify metastatic gastric cancer were created using administrative healthcare data from hospitalization, emergency department, and physician billing records. Time frames of data collection in the peri-diagnosis period, and the diagnosis codes used to identify metastatic disease were varied. Algorithm sensitivity, specificity, and accuracy were evaluated. RESULTS:Of 2366 gastric cancer patients, included within the chart review, 54.3% had metastatic disease. Algorithm sensitivity ranged from 50.0- 90%, specificity ranged from 27.6 - 92.5%, and accuracy from 61.5 - 73.4%. Sensitivity and specificity were maximized when the most conservative list of diagnosis codes from hospitalization and outpatient records in the six months prior to and the six months following diagnosis were included. CONCLUSION:Algorithms identifying metastatic gastric cancer can be used for research purposes using administrative healthcare data, although they are imperfect measures. The properties of these algorithms may be generalizable to other high fatality cancers and other healthcare systems. This study provides further support for the collection of population-based, TNM stage data.

SUBMITTER: Mahar AL

PROVIDER: S-EPMC5930789 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:PurposeThe modification of the cancer classification system aimed to improve the classical anatomy-based tumor, node, metastasis (TNM) staging by considering tumor biology, which is associated with patient prognosis, because such information provides additional precision and flexibility.Materials and methodsWe previously developed an mRNA expression-based single patient classifier (SPC) algorithm that could predict the prognosis of patients with stage II/III gastric cancer. We also validated its utilization in clinical settings. The prognostic single patient classifier (pSPC) differentiates based on 3 prognostic groups (low-, intermediate-, and high-risk), and these groups were considered as independent prognostic factors along with TNM stages. We evaluated whether the modified TNM staging system based on the pSPC has a better prognostic performance than the TNM 8th edition staging system. The data of 652 patients who underwent gastrectomy with curative intent for gastric cancer between 2000 and 2004 were evaluated. Furthermore, 2 other cohorts (n=307 and 625) from a previous study were assessed. Thus, 1,584 patients were included in the analysis. To modify the TNM staging system, one-grade down-staging was applied to low-risk patients according to the pSPC in the TNM 8th edition staging system; for intermediate- and high-risk groups, the modified TNM and TNM 8th edition staging systems were identical.ResultsAmong the 1,584 patients, 187 (11.8%), 664 (41.9%), and 733 (46.3%) were classified into the low-, intermediate-, and high-risk groups, respectively, according to the pSPC. pSPC prognoses and survival curves of the overall population were well stratified, and the TNM stage-adjusted hazard ratios of the intermediate- and high-risk groups were 1.96 (95% confidence interval [CI], 1.41-2.72; P<0.001) and 2.54 (95% CI, 1.84-3.50; P<0.001), respectively. Using Harrell's C-index, the prognostic performance of the modified TNM system was evaluated, and the results showed that its prognostic performance was better than that of the TNM 8th edition staging system in terms of overall survival (0.635 vs. 0.620, P<0.001).ConclusionsThe pSPC-modified TNM staging is an alternative staging system for stage II/III gastric cancer.

Project description:BackgroundThe pathological depth of tumor invasion (pT) and lymph node metastasis (pN) are critical independent prognostic factors for patients with gastric cancer, representing effective methods for evaluating prognosis. In this study, we employed a normalization weight combination score to calculate the weight ratio of the pT stage and pN stage. Subsequently, we established a novel wTN staging model based on these T and N weights, evaluating its prognostic capacity.MethodsThis study utilized a training cohort from A Medical University Cancer Hospital and a validation cohort from the SEER database. LASSO and Cox regression were employed to screen clinical characteristics. Multivariate linear regression and cluster analysis calculated the weight ratio of T stage and N stage in the training and validation cohorts, respectively, followed by re-staging. Prognostic value was evaluated using C-index, likelihood ratio, Wald, and Score tests for wTN stage and TNM stage. A nomogram model was developed, and accuracy was assessed using ROC, DCA, and RCS analyses.ResultsLASSO was used for initial screening, selecting 8 potential features for Cox analysis. Age, tumor size, MLNs, and tumor location were confirmed as independent prognostic factors. wTN was calculated in the training and validation cohorts, and nomograms were established with the independent factors. N stage had a higher weight proportion than T stage in both cohorts (0.625/0.375 in training cohort, 0.556/0.444 in validation cohort). wTN outperformed the 8th TNM stage in C-index, likelihood ratio, Wald, and Score tests in the training cohort, with successful validation in the validation cohort. Stratified analysis of distinct pathological types further demonstrates that wTN staging exhibits superior prognostic performance.ConclusionThe wTN staging model based on T stage and N stage weights has a good prognostic value for gastric cancer patients. The same conclusion was obtained in different pathological stratification.

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Validating an algorithm to identify metastatic gastric cancer in the absence of routinely collected TNM staging data.

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