Predicting obstructive sleep apnea severity in children referred for polysomnography: use of the Pediatric Sleep Questionnaire and Subscales.

PURPOSE: This study evaluated the role of the Pediatric Sleep Questionnaire (PSQ) and associated subscales in predicting the severity of obstructive sleep apnea (OSA) in children referred for attended polysomnography (PSG). METHODS: This is a retrospective study of children (0-18 years) who completed PSQs the night of their initial diagnostic PSG (2019-2020). We excluded children with previous PSG, positive airway pressure titrations, or underlying genetic or craniofacial syndromes. Area under the receiver operating characteristic curve (AUC [95%CIs]) were estimated for prediction of varying severities of obstructive apnea-hypopnea index (oAHI > 2, 5, 10, and 25/h) by the PSQ's sleep-related breathing disorders (SRBD) scale and subscales. RESULTS: Of 477 children, median (IQR) age at PSG was 5.7 (4.3); 60% of children were male, 21% were obese, and 4% had oAHI > 25/h. SRBD score did not improve discrimination of OSA cases at any oAHI threshold, with AUC CI that crossed 50% at all severities. Snoring subscale scores were predictive at oAHI > 2/h (AUC = 64.5% [59.5-69.5%]), oAHI > 5/h (AUC = 64.3% [59.6-69.0%]), and oAHI > 10 (AUC = 67.2% [62.0-72.4%]) thresholds, but were not predictive at oAHI > 25/h. The addition of demographic data (age and gender) improved the classification of the SRBD scale. CONCLUSIONS: When utilized in children referred for attended PSG due to concerns for an underlying sleep disorder, the PSQ snoring subscale was more predictive of OSA at varying thresholds than the SRBD scale. While the original intent of the PSQ was not for the purpose of predicting severity in children referred for PSG, future directions include augmenting the questionnaire with additional clinical variables.

Adiposity and cancer survival: a systematic review and meta-analysis.

PURPOSE: The increasing availability of clinical imaging tests (especially CT and MRI) that directly quantify adipose tissue has led to a rapid increase in studies examining the relationship of visceral, subcutaneous, and overall adiposity to cancer survival. To summarize this emerging body of literature, we conducted a systematic review and meta-analysis of imaging-measured as well as anthropometric proxies for adipose tissue distribution and cancer survival across a wide range of cancer types. METHODS: Using keywords related to adiposity, cancer, and survival, we conducted a systematic search of the literature in PubMed and MEDLINE, Embase, and Web of Science Core Collection databases from database inception to 30 June 2021. We used a random-effect method to calculate pooled hazard ratios (HR) and corresponding 95% confidence intervals (CI) within each cancer type and tested for heterogeneity using Cochran's Q test and the I2 test. RESULTS: We included 203 records for this review, of which 128 records were utilized for quantitative analysis among 10 cancer types: breast, colorectal, gastroesophageal, head and neck, hepatocellular carcinoma, lung, ovarian, pancreatic, prostate, and renal cancer. We found that imaging-measured visceral, subcutaneous, and total adiposity were not significantly associated with increased risk of overall mortality, death from primary cancer, or cancer progression among patients diagnosed with these 10 cancer types; however, we found significant or high heterogeneity for many cancer types. For example, heterogeneity was similarly high when the pooled HRs (95% CI) for overall mortality associated with visceral adiposity were essentially null as in 1.03 (0.55, 1.92; I2 = 58%) for breast, 0.99 (0.81, 1.21; I2 = 71%) for colorectal, versus when they demonstrated a potential increased risk 1.17 (0.85, 1.60; I2 = 78%) for hepatocellular carcinoma and 1.62 (0.90, 2.95; I2 = 84%) for renal cancer. CONCLUSION: Greater adiposity at diagnosis (directly measured by imaging) is not associated with worse survival among cancer survivors. However, heterogeneity and other potential limitations were noted across studies, suggesting differences in study design and adiposity measurement approaches, making interpretation of meta-analyses challenging. Future work to standardize imaging measurements and data analyses will strengthen research on the role of adiposity in cancer survival.