Based on Cardiopulmonary Exercise Testing to Construct and Validate Nomogram of Long-Term Prognosis Within 12 Months for NSCLC
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View abstract on PubMed
Summary
This summary is machine-generated.A new nomogram predicts long-term prognosis for non-small cell lung cancer (NSCLC) patients using cardiopulmonary exercise testing (CPET) data. This tool aids clinicians in making informed treatment decisions for better patient outcomes.
Area Of Science
- Oncology
- Pulmonary Medicine
- Surgical Prognostics
Background
- Accurate long-term prognosis prediction is crucial for non-small cell lung cancer (NSCLC) patient management.
- Cardiopulmonary exercise testing (CPET) provides valuable physiological data that may inform prognostic models.
Purpose Of The Study
- To develop and validate a nomogram for predicting long-term prognosis in NSCLC patients.
- To assess the predictive accuracy and discrimination ability of the developed nomogram.
Main Methods
- A retrospective study included 347 NSCLC patients who underwent pre-operative CPET.
- Data were split into training and validation cohorts for cross-validation.
- Nomogram performance was evaluated using concordance index (C-index), calibration curves, and receiver operating characteristic (ROC) curves (AUC).
Main Results
- The nomogram incorporated age, intraoperative blood loss, peak oxygen consumption (VO2 peak), and VE/VCO2 slope.
- The model demonstrated good discrimination and accuracy, with a C-index of 0.770.
- Area under the curve (AUC) for 6 and 12 months was 0.789 and 0.787, respectively, with sustained accuracy within 12 months.
Conclusions
- A novel nomogram based on CPET data was successfully developed for NSCLC prognosis.
- The nomogram exhibits robust discrimination and accuracy, offering a valuable tool for clinical decision-making.
- This predictive model can assist clinicians in tailoring treatment strategies for NSCLC patients.
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