Predicting non-response in patient-reported outcome measures: results from the Swiss quality assurance programme in cardiac inpatient rehabilitation

Background Quality assurance programmes measure and compare certain health outcomes to ensure high quality care in the health care sector. The outcome health related quality of life (HRQOL) is typically measured by patient-reported outcome measures (PROMs). However, certain patient groups are less likely to respond to PROMs than others. This non-response bias can potentially distort results in quality assurance programmes. Our study aims to identify relevant predictors for non-response during assessment using the PROM MacNew Heart Disease questionnaire in cardiac rehabilitation. Methods This is a cross-sectional study based on data from the Swiss external quality assurance programme. All patients aged 18 years or older who underwent inpatient cardiac rehabilitation in 16 Swiss rehabilitation clinics between 2016 and 2019 were included. Patients’ sociodemographic and basic medical data were analysed descriptively by comparing two groups: non-responders and responders. We used a random intercept logistic regression model to estimate associations of patient characteristics and clinic differences with non-response. Results Of 24 572 patients, there were 33.3% non-responders and 66.7% responders. The mean age was 70; 31.0% were women. The regression model showed that being female was associated with non-response (odds ratio (OR) 1.22; 95% confidence interval (95% CI) 1.14–1.30), as well as having no supplementary health insurance (OR 1.49; 95% CI 1.39–1.59). Each additional year of age increased the chance of non-response by an OR of 1.02 (95% CI 1.02–1.02). Not being a first language speaker of German, French, or Italian increased the chance of non-response by an OR of 6.94 (95% CI 6.03–7.99). Patients admitted directly from acute care had a higher chance of non-response (OR 1.23; 95% CI 1.10–1.38), as well as patients being discharged back into acute care after rehabilitation (OR 3.89; 95% CI 3.00–5.04). Each point on the cumulative illness rating scale (CIRS) total score increased the chance of non-response by an OR of 1.05 (95% CI 1.04–1.05). Certain diagnoses also influenced the chance of non-response. Even after adjustment for known confounders, response rates differed substantially between the 16 clinics. Conclusion We have found significant non-response bias among certain patient groups, as well as across different treatment facilities. Measures to improve response rates among patients with known barriers to participation, as well as among different treatment facilities need to be considered, particularly when PROMs are being used for comparison of providers in quality assurance programmes or outcome evaluation

Qualität aus Patientenperspektive

PROMs Dank Patient Reported Outcome Measures erhält die Patientenperspektive in der Qualitätsbeurteilung von Gesundheitseinrichtungen und -angeboten ihren festen Platz. Gleichzeitig stellen diese Indikatoren Health Care Professionals, Direktionen und Public-Health-Organisationen vor neue Herausforderungen

NOP10 predicts lung cancer prognosis and its associated small nucleolar RNAs drive proliferation and migration

Non-small cell lung cancer (NSCLC) is the leading cause of cancer death worldwide underlining the urgent need for new biomarkers and therapeutic targets for this disease. Long noncoding RNAs are critical players in NSCLC but the role of small RNA species is not well understood. In the present study, we investigated the role of H/ACA box small nucleolar RNAs (snoRNAs) and snoRNA-bound ribonucleoproteins (snoRNPs) in the tumorigenesis of NSCLC. H/ACA box snoRNPs including the NOP10 core protein were highly expressed in NSCLC. High levels of either NOP10 mRNA or protein were associated with poor prognosis in NSCLC patients. Loss of NOP10 and subsequent reduction of H/ACA box snoRNAs and rRNA pseudouridylation inhibited lung cancer cell growth, colony formation, migration, and invasion. A focused CRISPR/Cas9 snoRNA knockout screen revealed that genomic deletion of SNORA65, SNORA7A, and SNORA7B reduced proliferation of lung cancer cells. In line, high levels of SNORA65, SNORA7A, and SNORA7B were observed in primary lung cancer specimens with associated changes in rRNA pseudouridylation. Knockdown of either SNORA65 or SNORA7A/B inhibited growth and colony formation of NSCLC cell lines. Our data indicate that specific H/ACA box snoRNAs and snoRNA-associated proteins such as NOP10 have an oncogenic role in NSCLC providing new potential biomarkers and therapeutic targets for the disease