Thoracic Operations for Pulmonary Nodules Are Frequently Not Futile in Patients with Benign Disease
ABSTRACT Pulmonary nodules often require operative resection to obtain a diagnosis. However, 10 to 30% of operations result in a benign diagnosis. Our purpose was to determine whether negative thoracic operations are futile by describing the pathological diagnoses; determining new diagnoses and treatment changes initiated based on operative findings; and assessing morbidity, mortality, and cost of the procedure.
At our academic medical center, 278 thoracic operations were performed for known or suspected cancer between January 1, 2005, and April 1, 2009. We collected and summarized data pertaining to preoperative patient and nodule characteristics, pathologic diagnosis, postoperative treatment changes resulting from surgical resection, perioperative morbidity and mortality, and hospital charges for patients with benign pathology.
Twenty-three percent (65/278) of patients who underwent surgical resection for a suspicious nodule had benign pathology. We report granulomatous disease in 57%, benign tumors in 15%, fibrosis in 12%, and autoimmune and vascular diseases in 9%. Definitive diagnosis or treatment changes occurred in 85% of cases. Surgical intervention led to a new diagnosis in 69%, treatment course changes in 68% of benign cases, medication changes in 38%, new consultation in 31%, definitive treatment in 9%, and underlying disease management in 34%. There was no intraoperative, in-hospital, or 30-day mortality. Postoperative in-hospital events occurred in seven patients. The mean total cost was $25,515 with a mean cost per day of $7618.
Patients with a benign diagnosis after surgical resection for a pulmonary nodule received a new diagnosis or had a treatment course change in 85% of the cases.
- SourceAvailable from: Pascal Alexandre ThomasRevue des Maladies Respiratoires 01/2014; DOI:10.1016/j.rmr.2013.10.641 · 0.49 Impact Factor
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ABSTRACT: Background. Patients presenting to thoracic surgeons with pulmonary nodules suggestive of lung cancer have varied diagnostic options including navigation bronchoscopy (NB), computed tomography-guided fine-needle aspiration (CT-FNA), F-18-fluoro-deoxyglucose positron emission tomography (FDG-PET) and video-assisted thoracoscopic surgery (VATS). We studied the relative cost-effective initial diagnostic strategy for a 1.5- to 2-cm nodule suggestive of cancer. Methods. A decision analysis model was developed to assess the costs and outcomes of four initial diagnostic strategies for diagnosis of a 1.5- to 2-cm nodule with either a 50% or 65% pretest probability of cancer. Medicare reimbursement rates were used for costs. Quality-adjusted life years were estimated using patient survival based on pathologic staging and utilities derived from the literature. Results. When cancer prevalence was 65%, tissue acquisition strategies of NB and CT-FNA had higher quality-adjusted life years compared with either FDG-PET or VATS, and VATS was the most costly strategy. In sensitivity analyses, NB and CT-FNA were more cost-effective than FDG-PET when FDG-PET specificity was less than 72%. When cancer prevalence was 50%, NB, CT-FNA, and FDG-PET had similar cost-effectiveness. Conclusions. Both NB and CT-FNA diagnostic strategies are more cost-effective than either VATS biopsy or FDG-PET scan to diagnose lung cancer in moderate-to high-risk nodules and resulted in fewer nontherapeutic operations when FDG-PET specificity was less than 72%. An FDG-PET scan for diagnosis of lung cancer may not be cost-effective in regions of the country where specificity is low. (C) 2014 by The Society of Thoracic SurgeonsThe Annals of Thoracic Surgery 07/2014; DOI:10.1016/j.athoracsur.2014.05.025 · 3.63 Impact Factor
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ABSTRACT: Background: Existing predictive models for lung cancer focus on improving screening or referral for biopsy in general medical populations. A predictive model calibrated for use during preoperative evaluation of suspicious lung lesions is needed to reduce unnecessary operations for a benign disease. A clinical prediction model (Thoracic Research Evaluation And Treatment [TREAT]) is proposed for this purpose. Methods: We developed and internally validated a clinical prediction model for lung cancer in a prospective cohort evaluated at our institution. Best statistical practices were used to construct, evaluate, and validate the logistic regression model in the presence of missing covariate data using bootstrap and optimism corrected techniques. The TREAT model was externally validated in a retrospectively collected Veteran Affairs population. The discrimination and calibration of the model was estimated and compared with the Mayo Clinic model in both the populations. Results: The TREAT model was developed in 492 patients from Vanderbilt whose lung cancer prevalence was 72% and validated among 226 Veteran Affairs patients with a lung cancer prevalence of 93%. In the development cohort, the area under the receiver operating curve (AUC) and Brier score were 0.87 (95% confidence interval [CI], 0.83-0.92) and 0.12, respectively compared with the AUC 0.89 (95% CI, 0.79-0.98) and Brier score 0.13 in the validation dataset. The TREAT model had significantly higher accuracy (p < 0.001) and better calibration than the Mayo Clinic model (AUC = 0.80; 95% CI, 75-85; Brier score = 0.17). Conclusion: The validated TREAT model had better diagnostic accuracy than the Mayo Clinic model in preoperative assessment of suspicious lung lesions in a population being evaluated for lung resection.Journal of thoracic oncology: official publication of the International Association for the Study of Lung Cancer 08/2014; 9(10). DOI:10.1097/JTO.0000000000000287 · 5.80 Impact Factor