Polysomnographic Markers of Obstructive Sleep Apnea Severity and Cancer-Related Mortality: A Large Retrospective Multicenter Clinical Cohort Study

RATIONALE

The evidence for an association between cancer survival and obstructive sleep apnea (OSA) remains under-explored.

OBJECTIVES

To evaluate an association between markers of OSA severity (respiratory disturbances, hypoxemia, and sleep fragmentation) and cancer-related mortality in individuals with previously diagnosed cancer.

METHODS

We conducted a multicenter retrospective cohort study using linked clinical and provincial health administrative data on consecutive adults who underwent a diagnostic sleep study between 1994 and 2017 in four Canadian academic hospitals and were previously diagnosed with cancer through the Ontario Cancer Registry. Multivariable cause-specific Cox regressions were utilized to address the research objective.

RESULTS

We included 2,222 subjects. Over a median follow-up time of 5.6 years (IQR: 2.7-9.1), 261/2,222 (11.7%) individuals with prevalent cancer died from cancer-related causes, which accounted for 44.2% (261/590) of all-cause death. Controlling for age, sex, alcohol use disorder, prior heart failure, COPD, hypertension, diabetes, treatment for OSA, clinic site, year of the sleep study, and time since the cancer diagnosis, measures of hypoxemia and sleep fragmentation, but not apnea-hypopnea index were significantly associated with the cancer-specific mortality: % time spent with SaO2 <90% (HR per 5% increase: 1.05; 95% CI: 1.01-1.09); mean SaO2 (HR per 3% increase: 0.79; 0.68-0.92); and % of Stage 1 Sleep (HR per 16% increase: 1.27; 1.07-1.51).

CONCLUSION

In a large clinical cohort of adults with suspected OSA and previously diagnosed cancer, measures of nocturnal hypoxemia and sleep fragmentation as markers of OSA severity were significantly associated with cancer-related mortality, suggesting the need for more targeted risk awareness.

Case-Ascertainment Models to Identify Adults with Obstructive Sleep Apnea Using Health Administrative Data: Internal and External Validation

Background

There is limited evidence on whether obstructive sleep apnea (OSA) can be accurately identified using health administrative data.

Study Design and Methods

We derived and validated a case-ascertainment model to identify OSA using linked provincial health administrative and clinical data from all consecutive adults who underwent a diagnostic sleep study (index date) at two large academic centers (Ontario, Canada) from 2007 to 2017. The presence of moderate/severe OSA (an apnea–hypopnea index≥15) was defined using clinical data. Of 39 candidate health administrative variables considered, 32 were tested. We used classification and regression tree (CART) methods to identify the most parsimonious models via cost-complexity pruning. Identified variables were also used to create parsimonious logistic regression models. All individuals with an estimated probability of 0.5 or greater using the predictive models were classified as having OSA.

Results

The case-ascertainment models were derived and validated internally through bootstrapping on 5099 individuals from one center (33% moderate/severe OSA) and validated externally on 13,486 adults from the other (45% moderate/severe OSA). On the external cohort, parsimonious models demonstrated c-statistics of 0.75–0.81, sensitivities of 59–60%, specificities of 87–88%, positive predictive values of 79%, negative predictive values of 73%, positive likelihood ratios (+LRs) of 4.5–5.0 and –LRs of 0.5. Logistic models performed better than CART models (mean integrated calibration indices of 0.02–0.03 and 0.06–0.12, respectively). The best model included: sex, age, and hypertension at the index date, as well as an outpatient specialty physician visit for OSA, a repeated sleep study, and a positive airway pressure treatment claim within 1 year since the index date.

Interpretation

Among adults who underwent a sleep study, case-ascertainment models for identifying moderate/severe OSA using health administrative data had relatively low sensitivity but high specificity and good discriminative ability. These findings could help study trends and outcomes of OSA individuals using routinely collected health care data.

Comparing the Excessive Daytime Sleepiness of Obese and Non-obese Patients

BACKGROUND

Obesity, particularly morbid obesity, has various physical and mental complications. Excessive daytime somnolence (EDS) is a sleep disorder that reduces individuals' performance capability and the accuracy of their short-term memory and causes learning problems. This retrospective study aimed to document the presence of EDS in a sample of obese patients in comparison to patients with a normal weight.

OBJECTIVES

This article compares the excessive daytime sleepiness of obese and non-obese patients in the minimally invasive surgery research center in Tehran, Iran.

PATIENTS AND METHODS

In this case-control study, we compared excessive daytime sleepiness in 55 obese patients who were candidates for laparoscopic surgery, with a body mass index (BMI) of equal to or greater than 30 kg/ m2, with 55 controls with a normal BMI (19.5 - 24.9 kg/ m2). The process of selecting the control group in our case-control study is matching in group levels, so that the controls are similar to the case group with regard to certain key characteristics, such as age, sex, and race. The sleep assessment was based on the Epworth sleepiness scale (ESS) questionnaire. Analysis of variance (ANOVA) was used to compare the means of quantitative data, such as the ESS score of groups.

RESULTS

Sleepiness was not affected by gender in cases or controls. The sleepiness prevalence was 29 (52.7%) in the cases group and 17 (30.9%) in the control group (OR = 2.493 (95% CI 1.144 -5.435)). The mean ESS scores in cases and controls were 7.82 ± 3.86 and 10.54 ± 6.15, respectively (P = 0.007). Moreover, the prevalence of sleepiness and the mean ESS scores in class III of obesity differed significantly from the controls (16 (57.1%) vs. 17 (30.9%)) (OR = 2.980 (95% CI 1.162 - 7.645)) and (11.04 ± 5.93 vs. 7.82 ± 3.86) (P = 0.013), respectively.

CONCLUSIONS

Our findings suggest a strong relationship between EDS and obesity, particularly morbid obesity. Therefore, physicians must be familiar with EDS as a mixed clinical entity indicating careful assessment and specific treatment planning.

Untreated obstructive sleep apnea and the risk for serious long-term adverse outcomes: a systematic review

BACKGROUND

Reports on the association between obstructive sleep apnea (OSA) and risk of death, cardiovascular (CV) events, diabetes and depression have been inconsistent.

METHODS

We conducted a systematic review of the prognostic value of clinical and polysomnographic (PSG) characteristics of OSA for adverse long-term outcomes of untreated OSA in adult patients. A comprehensive search strategy for prognosis studies, OSA, CV events, mortality, depression and diabetes was developed in collaboration with a medical information specialist. All English language studies, from Jan 1999 to Dec 2011, with longitudinal design in adults with OSA diagnosed by PSG recording, found through Medline, Embase and bibliographies of identified articles, were considered eligible. Quality was assessed using published guidelines.

RESULTS

Among 26 articles, ten evaluated the association of OSA with mortality, 9 with a composite CV outcome, 4 with stroke, 2 with diabetes and 1 with depression. Significant relationships between the apnea-hypopnea index (AHI) and outcomes of interest were reported in 18 studies: seven for all-cause mortality, six for composite CV events, three for stroke, one for diabetes and one for depression. The effect of AHI was attenuated by female gender, older age, absence of daytime sleepiness and higher body mass index. Due to clinical heterogeneity between studies, meta-analyses were not performed.

CONCLUSION

Evidence exists in men for a relationship between OSA and all-cause mortality and a composite CV outcome. Associations between OSA and other outcomes remain uncertain. Among OSA-specific markers, only AHI was a consistent predictor. Other consistent predictors were traditional CV risk factors. Research is required to identify effect modifiers and the predictive ability of various AHI threshold values and hypopnea definitions. An enhanced set of OSA-specific predictors will allow better risk stratification to guide OSA treatment.