ArticleInteractive cardiovascular and thoracic surgery2021
Is the Yedikule-solitary pulmonary nodule malignancy risk score sufficient to predict malignancy? An internal validation study.
Article in Interactive cardiovascular and thoracic surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Incidence and risk factors for malignancy in patients with incidental solitary pulmonary nodules: a systematic review and meta-analysis.Annals of medicine · 2026Pooled it
- Could the probability of surgical indication be determined after first episode of primary spontaneous pneumothorax?General thoracic and cardiovascular surgery · 2023Trial
- The Stapler Dilemma in VATS Wedge Resection: Are Sutures a Viable Alternative?Journal of clinical medicine · 2025Article
- Application of CT Postprocessing Reconstruction Technique in Differential Diagnosis of Benign and Malignant Solitary Pulmonary Nodules and Analysis of Risk Factors.Computational and mathematical methods in medicine · 2022Article
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8 authors.
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Abstract
objectivesWe aimed to develop a malignancy risk score model for solitary pulmonary nodules (SPNs) using the demographic, radiological and clinical characteristics of patients in our centre. The model was then internally validated for malignancy risk estimation.
methodsA total of 270 consecutive patients who underwent surgery for SPN between June 2017 and May 2019 were retrospectively analysed. Using the receiver operating characteristic curve analysis, cut-off values were determined for radiological tumour diameter, maximum standardized uptake value and the Brock University probability of malignancy (BU-PM) model. The Yedikule-SPN malignancy risk model was developed using these cut-off values and demographic, radiological and clinical criteria in the first 180 patients (study cohort) and internally validated with the next 90 patients (validation cohort). The Yedikule-SPN model was then compared with the BU-PM model in terms of malignancy prediction.
resultsMalignancy was reported in 171 patients (63.3%). Maximum standardized uptake value and BU-PM scores were sufficient to predict malignancy (P < 0.001 for both), while the effectiveness of nodule size determined on thoracic computed tomography did not reach statistical significance (P = 0.09). When the Yedikule-SPN model developed with the study cohort was applied to the validation cohort, it significantly predicted malignancy (area under the receiver operating characteristic curve: 0.883, 95% confidence interval: 0.827-0.957, P < 0.001). Comparison of patients in the validation group with Yedikule-SPN scores above (n = 53) and below (n = 37) the cut-off value of 65.75 showed that the malignancy rate was significantly higher among patients with Yedikule-SPN score over 65.75 (86.8% vs 21.6%, P < 0.001, odds ratio = 23.821, 95% confidence interval: 7.805-72.701). When compared with the BU-PM model in all patients, the Yedikule-SPN model tended to be a better predictor of malignancy (P = 0.06).
conclusionsThe internally validated Yedikule-SPN model is also a good predictor of the malignancy of SPN(s). Prospective and multicentre external validation studies with large patients' cohorts are needed.
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