Model-based versus clinical prediction of the spirometric response to lung volume reduction surgery

Prognostic models for outcome prediction in patients with chronic obstructive pulmonary disease: systematic review and critical appraisal

OBJECTIVE

To map and assess prognostic models for outcome prediction in patients with chronic obstructive pulmonary disease (COPD).

DESIGN

Systematic review.

DATA SOURCES

PubMed until November 2018 and hand searched references from eligible articles.

ELIGIBILITY CRITERIA FOR STUDY SELECTION

Studies developing, validating, or updating a prediction model in COPD patients and focusing on any potential clinical outcome.

RESULTS

The systematic search yielded 228 eligible articles, describing the development of 408 prognostic models, the external validation of 38 models, and the validation of 20 prognostic models derived for diseases other than COPD. The 408 prognostic models were developed in three clinical settings: outpatients (n=239; 59%), patients admitted to hospital (n=155; 38%), and patients attending the emergency department (n=14; 3%). Among the 408 prognostic models, the most prevalent endpoints were mortality (n=209; 51%), risk for acute exacerbation of COPD (n=42; 10%), and risk for readmission after the index hospital admission (n=36; 9%). Overall, the most commonly used predictors were age (n=166; 41%), forced expiratory volume in one second (n=85; 21%), sex (n=74; 18%), body mass index (n=66; 16%), and smoking (n=65; 16%). Of the 408 prognostic models, 100 (25%) were internally validated and 91 (23%) examined the calibration of the developed model. For 286 (70%) models a model presentation was not available, and only 56 (14%) models were presented through the full equation. Model discrimination using the C statistic was available for 311 (76%) models. 38 models were externally validated, but in only 12 of these was the validation performed by a fully independent team. Only seven prognostic models with an overall low risk of bias according to PROBAST were identified. These models were ADO, B-AE-D, B-AE-D-C, extended ADO, updated ADO, updated BODE, and a model developed by Bertens et al. A meta-analysis of C statistics was performed for 12 prognostic models, and the summary estimates ranged from 0.611 to 0.769.

CONCLUSIONS

This study constitutes a detailed mapping and assessment of the prognostic models for outcome prediction in COPD patients. The findings indicate several methodological pitfalls in their development and a low rate of external validation. Future research should focus on the improvement of existing models through update and external validation, as well as the assessment of the safety, clinical effectiveness, and cost effectiveness of the application of these prognostic models in clinical practice through impact studies.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42017069247.

A Patient with GOLD Stage 3 COPD « cured » by One-Way Endobronchial Valves

Lung hyperinflation is a main determinant of dyspnoea in patients with chronic obstructive pulmonary disease (COPD). Surgical or bronchoscopic lung volume reduction are the most efficient therapeutic approaches for reducing hyperinflation in selected patients with emphysema. We here report the case of a 69-year old woman with COPD (GOLD stage 3-D) referred for lung volume reduction. She complained of persistent disabling dyspnoea despite appropriate therapy. Chest imaging showed marked emphysema heterogeneity as well as severe hyperinflation of the right lower lobe. She was deemed to be a good candidate for bronchoscopic treatment with one-way endobronchial valves. In the absence of interlobar collateral ventilation, 2 endobronchial valves were placed in the right lower lobe under general anaesthesia. The improvement observed 1 and 3 months after the procedure was such that the patient no longer met the pulmonary function criteria for COPD. The benefit persisted after 3 years.

A comprehensive review of predictive and prognostic composite factors implicated in the heterogeneity of treatment response and outcome across disease areas

AIM

To assess and present the current body of evidence regarding composite measures associated with differential treatment response or outcome as a result of patient heterogeneity and to evaluate their consistency across disease areas.

METHODS

A comprehensive review of the literature from the last 10 years was performed using three databases (PubMed, Embase and Cochrane). All articles that met the inclusion/exclusion criteria were selected, abstracted and assessed using the NICE level-of-evidence criteria.

RESULTS

Forty-nine studies were identified in the data abstraction. Approximately one-third focused on existing composite measures, and the rest investigated emerging composite factors. The majority of studies targeted patients with cancer, cardiovascular disease or psychological disorders. As a whole, the composite measures were found to be disease-specific, but some composite elements, including age, gender, comorbidities and health status, showed consistency across disease areas. To complement these findings, common individual factors found in five previous independent disease-specific literature assessments were also summarised, including age, gender, treatment adherence and satisfaction, healthcare resource utilisation and health status.

CONCLUSIONS

Composite measures can play an important role in characterising heterogeneity of treatment response and outcome in patients suffering from various medical conditions. These measures can help clinicians to better distinguish between patients with high likelihood to respond well to treatment and patients with minimal chances of positive therapeutic outcomes. Herein, the individual factors identified can be used to develop novel predictive or prognostic composite measures that can be applicable across disease areas. Reflecting these cross-disease measures in clinical and public health decisions has the distinctive appeal to enable targeted treatment for patients suffering from multiple medical conditions, which may ultimately yield significant gains in individual outcomes, population health and cost-effective resource allocation.