Survival of 2,991 Patients With Surgical Lung Cancer

Computer-assisted diagnosis for an early identification of lung cancer in chest X rays

Computer-assisted diagnosis (CAD) algorithms have shown its usefulness for the identification of pulmonary nodules in chest x-rays, but its capability to diagnose lung cancer (LC) is unknown. A CAD algorithm for the identification of pulmonary nodules was created and used on a retrospective cohort of patients with x-rays performed in 2008 and not examined by a radiologist when obtained. X-rays were sorted according to the probability of pulmonary nodule, read by a radiologist and the evolution for the following three years was assessed. The CAD algorithm sorted 20,303 x-rays and defined four subgroups with 250 images each (percentiles ≥ 98, 66, 33 and 0). Fifty-eight pulmonary nodules were identified in the ≥ 98 percentile (23,2%), while only 64 were found in lower percentiles (8,5%) (p < 0.001). A pulmonary nodule was confirmed by the radiologist in 39 out of 173 patients in the high-probability group who had follow-up information (22.5%), and in 5 of them a LC was diagnosed with a delay of 11 months (12.8%). In one quarter of the chest x-rays considered as high-probability for pulmonary nodule by a CAD algorithm, the finding is confirmed and corresponds to an undiagnosed LC in one tenth of the cases.

Is there a survival advantage of incomplete resection of non-small-cell lung cancer that is found to be unresectable at thoracotomy?

A best evidence topic in thoracic surgery was written according to a structured protocol. The question addressed was: in patients with non-small-cell lung cancer that is found to be unresectable at thoracotomy, is incomplete resection superior for achieving survival advantage? Altogether more than 400 papers were found using the reported search, of which nine represented the best evidence to answer the clinical question. The authors, journal, date and country of publication, patient group studied, study type, relevant outcomes and results of these papers were tabulated. In total, data from an estimated 1083 patients were analysed. Three-year survival rates varied from 0 to 22% in incomplete resection and from 0 to 10% in exploratory thoracotomy. Median survival ranged from 6.5 to 19.1 months in incomplete resection and from 5.3 to 17 months in exploratory thoracotomy. The majority of studies (8/9) found survival in incomplete resection to be superior. However, only 3/9 studies presented statistical analysis of results. The largest of these found superior postoperative survival in incomplete resection (including residual nodal disease), one study showed a significant survival difference for R1 but not R2 resection and another with small patient numbers (n = 29) found no significant difference. We conclude that the best evidence suggests that there may be a survival advantage from incomplete resection of non-small-cell lung cancer when there is microscopic (R1) or nodal residual disease, but not when macroscopic residual (R2) disease remains.

Stereotactic ablative body radiotherapy (SABR) for primary and secondary lung tumours

Stereotactic ablative body radiotherapy (SABR) represents a technological breakthrough in radiotherapy technique, with proven benefits to patients in terms of improved tumour control and overall survival. The key components of SABR are described. The current evidence base for SABR for the treatment of primary and secondary lung tumours is appraised, and key ongoing trials are identified.

4-year mortality in patients with non-small-cell lung cancer: development and validation of a prognostic index

BACKGROUND

Lung cancer is the commonest cause of death due to cancer in the world. Non-small-cell lung carcinoma (NSCLC) represents about 80% of overall lung cancer cases worldwide. An accurate predictive model of mortality in patients with NSCLC could be useful to clinicians, policy makers, and researchers involved in risk stratification. The objective of this study was to develop and validate a simple prognostic index for 4-year mortality in patients with NSCLC by use of information obtained at the time of lung cancer diagnosis.

METHODS

In 2000, 4669 patients with histologically or cytologically proven NSCLC were enrolled prospectively from 137 pneumology departments in French general hospitals. Patients not lost to follow-up (n=4479) were randomly assigned to the development cohort (n=2979) or the validation cohort (n=1500). Every patient's physician completed a standard and anonymous questionnaire. We used a Cox model to identify variables independently associated with mortality and weighted the variables to create a prognostic index.

FINDINGS

Median follow-up for survivors was 49 months (IQR 46-51). There were 2585 deaths (87%) in the development cohort and 1310 deaths (87%) in the validation cohort. Five independent predictors of mortality were identified: age (>70 years, 1 point); sex (male, 1 point); performance status at diagnosis (reduced activity, 3 points; active >50%, 5 points; inactive >50%, 8 points; and total incapacity, 10 points); histological type (large-cell carcinoma, 2 points); and tumour-node-metastasis (TNM) staging system (IIA or IIB, 3 points; IIIA or IIIB, 6 points; and IV, 8 points). The minimum and maximum possible point scores were 0 and 22, respectively. Scores of the prognostic index were strongly associated with 4-year mortality in the development cohort: 0-1 points predicted a 35% (95% CI 28-43) risk, 2-4 points a 59% (52-66) risk, 5-7 points a 77% (72-81) risk, 8-10 points an 88% (85-90) risk, 11-14 points a 97% (96-98) risk, and 15-22 points a 99% (97-100) risk. The corresponding percentages in the validation cohort were 36% (24-47), 60% (50-70), 77% (71-83), 89% (86-93), 96% (95-98), and 99% (98-100), respectively. The prognostic index showed good discrimination, with mean bootstrap c statistics of 0.85 (95% CI 0.84-0.86) in the development cohort and 0.86 (95% CI 0.85-0.87) in the validation cohort.

INTERPRETATION

This prognostic index, incorporating personal, tumour, and functional information would be helpful in guiding patient management, resource use, and the design of clinical trials.