Quality of Life in the High-Risk Candidate for Lung Resection

Poor preoperative patient-reported quality of life is associated with complications following pulmonary lobectomy for lung cancer

Objectives

To assess whether quality of life (QOL) was associated with cardiopulmonary complications following pulmonary lobectomy for lung cancer.

Methods

Retrospective analysis of 200 consecutive patients who had pulmonary lobectomy for lung cancer (September 2014-October 2015). QOL was assessed by the self-administration of the European Organisation for Research and Treatment of Cancer QLQ-C30 questionnaire within 2 weeks before the operation. The individual QOL scales were tested for a possible association with cardiopulmonary complications along with other objective baseline and surgical parameters by univariable and multivariable analyses.

Results

Forty-three patients (21.5%) developed postoperative cardiopulmonary complications; 4 of them died within 30 days (2%). Univariable analysis showed that, compared to patients without complications, those with complications reported a lower global health status (GHS) [59.1; standard deviation (SD) 27.2 vs 69.6; SD 20.6, P  =   0.02], were older (71.2; SD 8.4 vs 67.7; SD 9.4, P  =   0.03), had lower values of forced expiratory volume in one second (FEV1) (83.9; SD 27.2 vs 91.4; SD 20.9), P  =   0.06) and carbon monoxide lung diffusion capacity (DLCO) (67.9; SD 20.9 vs 74.2; SD 17.6, P  =   0.02) and higher performance score (0.76; SD 0.63 vs 0.53; SD 0.64, P  =   0.02). Stepwise logistic regression analysis showed that factors independently associated with cardiopulmonary complications were age [odds ratio (OR) 1.04, 95% CI 1.0-1.09, P  =   0.02] and patient-reported GHS [OR 0.98, 95% confidence interval (CI) 0.96-0.99, P  =   0.006], whereas other objective parameters (i.e. FEV1, DLCO) were not. The best cut-off value for GHS to discriminate patients with complications after surgery was 50 (c-index 0.65, 95% CI 0.58-0.72).

Conclusions

A poor GHS perceived by the patient was associated with postoperative cardiopulmonary morbidity. Patient perceptions and values should be included in the risk stratification process to tailor cancer treatment.

The impact of perceived frailty on surgeons' estimates of surgical risk

BACKGROUND

Physicians are only moderately accurate in estimating surgical risk based on clinical vignettes. We assessed the impact of perceived frailty by measuring the influence of a short video of a standardized patient on surgical risk estimates.

METHODS

Thoracic surgeons and cardiothoracic trainees estimated the risk of major complications for lobectomy based on clinical vignettes of varied risk categories (low, average, high). After each vignette, subjects viewed a randomly selected video of a standardized patient exhibiting either vigorous or frail behavior, then reestimated risk. Subjects were asked to rate 5 vignettes paired with 5 different standardized patients.

RESULTS

Seventy-one physicians participated. Initial risk estimates varied according to the vignette risk category: low 15.2%±11.2% risk; average 23.7%±16.1%; high 37.3%±18.9% (p<0.001 by analysis of variance). Concordant information in vignettes and videos moderately altered estimates (high risk vignette, frail video 10.6%±27.5% increase in estimate, p=0.006; low risk vignette, vigorous video 14.5%±45.0% decrease, p=0.009). Discordant findings influenced risk estimates more substantially (high risk vignette, vigorous video 21.2%±23.5% decrease in second risk estimate, p<0.001; low risk vignette, frail video 151.9%±209.8% increase, p<0.001).

CONCLUSIONS

Surgeons differentiated relative risk of lobectomy based on clinical vignettes. The effect of viewing videos was small when vignettes and videos were concordant; the effect was more substantial when vignettes and videos were discordant. The information will be helpful in training future surgeons in frailty recognition and risk estimation.

Can we predict morbidity and mortality before an operation?

Estimation of perioperative morbidity and mortality has been the subject of numerous studies in patients undergoing major lung resection. Multivariate models have been developed with the goal of improving patient selection for surgery, especially with recent impetus for systems-based quality improvement and a need to provide high-quality data for evidence-based decision making for high-risk patients. This article explores relationships between the variables studied and predictors of outcome, and discusses if it is ever possible to accurately predict risk of morbidity and mortality after major lung resection.