ArticleThe clinical respiratory journal2024
Based on Cardiopulmonary Exercise Testing to Construct and Validate Nomogram of Long-Term Prognosis Within 12 Months for NSCLC.
Article in The clinical respiratory journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Grading the evidence for CPET variables in predicting perioperative morbidity and long-term mortality in lung cancer surgery: a systematic review and meta-analysis.Systematic reviews · 2026Pooled it
- Development and internal validation of a risk model for hyperuricemia among people living with HIV in Hangzhou, China: a retrospective longitudinal cohort study.Frontiers in endocrinology · 2026Article
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Authors and funding
8 authors.
Funding
Abstract
objectiveConstruction nomogram was to effectively predict long-term prognosis in patients with non-small cell lung cancer (NSCLC). MATERIALS AND
methodsThe nomogram is developed by a retrospective study of 347 patients with NSCLC who underwent cardiopulmonary exercise testing (CPET) before surgery from May 2019 to February 2022. Cross-validation divided the data into a training cohort and validation cohort. The discrimination and accuracy ability of the nomogram were proofed by concordance index (C-index), calibration curve, receiver operating characteristic (ROC) curve, the area under the curve (AUC), and time-dependent ROC in validation cohort.
resultsAge, intraoperative blood loss, VO
conclusionWe developed a nomogram based on CPET. This model has a good ability of discrimination and accuracy. It could help clinicians to make treatment decision in clinical decision.
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Registered trials
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