METHODS: This study included 344 patients from the Korean Obstructive Lung Disease (KOLD) cohort. External validation was performed on a cohort of 112 patients. In total, 525 chest CT-based radiomics features were semi-automatically extracted. The five most useful features for survival prediction were selected by least absolute shrinkage and selection operation (LASSO) Cox regression analysis and used to generate a RS. The ability of the RS for classifying COPD patients into high or low mortality risk groups was evaluated with the Kaplan-Meier survival analysis and Cox proportional hazards regression analysis.
RESULTS: The five features remaining after the LASSO analysis were %LAA-950, AWT_Pi10_6th, AWT_Pi10_heterogeneity, %WA_heterogeneity, and VA18mm. The RS demonstrated a C-index of 0.774 in the discovery group and 0.805 in the validation group. Patients with a RS greater than 1.053 were classified into the high-risk group and demonstrated worse overall survival than those in the low-risk group in both the discovery (log-rank test, < 0.001; hazard ratio [HR], 5.265) and validation groups (log-rank test, < 0.001; HR, 5.223). For both groups, RS was significantly associated with overall survival after adjustments for patient age and body mass index.
CONCLUSIONS: A radiomics approach for survival prediction and risk stratification in COPD patients is feasible, and the constructed radiomics model demonstrated acceptable performance. The RS derived from chest CT data of COPD patients was able to effectively identify those at increased risk of mortality.
KEY POINTS: • A total of 525 chest CT-based radiomics features were extracted and the five radiomics features of %LAA-950, AWT_Pi10_6th, AWT_Pi10_heterogeneity, %WA_heterogeneity, and VA18mm were selected to generate a radiomics model. • A radiomics model for predicting survival of COPD patients demonstrated reliable performance with a C-index of 0.774 in the discovery group and 0.805 in the validation group. • Radiomics approach was able to effectively identify COPD patients with an increased risk of mortality, and patients assigned to the high-risk group demonstrated worse overall survival in both the discovery and validation groups.
DESIGN: This is a multisite observational study.
SETTING: The study was conducted in four tertiary care hospitals in Australia.
SUBJECTS: A total of 225 participants, following cardiac surgery, were involved in the study.
INTERVENTION: Participants completed the original 13-item FDQ and other measures of physical function, pain and health-related quality of life.
METHOD: Item reduction was utilized to develop the shortened version. Reliability was evaluated using intraclass correlation coefficients (ICCs), the smallest detectable change and Bland-Altman plots. The validity and responsiveness were evaluated using correlation. Anchor and distribution-based calculation was used to calculate the minimal clinical important difference (MCID).
RESULTS: Item reduction resulted in the creation of a 10-item shortened version of the questionnaire (FDQ-s). Within the cohort of cardiac surgery patient, the mean (SD) for the FDQ-s was 38.7 (19.61) at baseline; 15.5 (14.01) at four weeks and 7.9 (12.01) at three months. Validity: excellent internal consistency (Cronbach's α > 0.90) and fair-to-excellent construct validity (>0.4). Reliability: internal consistency was excellent (Cronbach's α > 0.8). The FDQ-s had excellent test-retest reliability (ICC = 0.89-0.92). Strong responsiveness overtime was demonstrated with large effect sizes (Cohen's d > 1.0). The MCID of the FDQ-s was calculated between 4 and 10 out of 100 (in cm).
CONCLUSION: The FDQ-s demonstrated robust psychometric properties as a measurement tool of physical function of the thoracic region following cardiac surgery.