The objective of the present study is to compare the QL of a wide range of chronic disease patients. Secondary analysis of eight existing data sets, including over 15,000 patients, was performed. The studies were conducted between 1993 and 1996 and included population-based samples, referred samples, consecutive samples, and/or consecutive samples. The SF-36 or SF-24 were employed as generic QL instruments. Patients who were older, female, had a low level of education, were not living with a partner, and had at least one comorbid condition, in general, reported the poorest level of QL. On the basis of rank ordering across the QL dimensions, three broad categories could be distinguished. Urogenital conditions, hearing impairments, psychiatric disorders, and dermatologic conditions were found to result in relatively favorable functioning. A group of disease clusters assuming an intermediate position encompassed cardiovascular conditions, cancer, endocrinologic conditions, visual impairments, and chronic respiratory diseases. Gastrointestinal conditions, cerebrovascular/neurologic conditions, renal diseases, and musculoskeletal conditions led to the most adverse sequelae. This categorization reflects the combined result of the diseases and comorbid conditions. If these results are replicated and validated in future studies, they can be considered in addition to information on the prevalence of the diseases, potential benefits of care, and current disease-specific expenditures. This combined information will help to better plan and allocate resources for research, training, and health care.

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BackgroundIn January 2017, the Dutch cervical cancer screening programme transitioned from cytomorphological to primary high-risk HPV (hrHPV) DNA screening, including the introduction of self-sampling, for women aged between 30 and 60 years. The Netherlands was the first country to switch to hrHPV screening at the national level. We investigated the health impact of this transition by comparing performance indicators from the new hrHPV-based programme with the previous cytology-based programme.MethodsWe obtained data from the Dutch nationwide network and registry of histo- and cytopathology (PALGA) for 454,573 women eligible for screening in 2017 who participated in the hrHPV-based programme between 1 January 2017 and 30 June 2018 (maximum follow-up of almost 21 months) and for 483,146 women eligible for screening in 2015 who participated in the cytology-based programme between 1 January 2015 and 31 March 2016 (maximum follow-up of 40 months). We compared indicators of participation (participation rate), referral (screen positivity; referral rate) and detection (cervical intraepithelial neoplasia (CIN) detection; number of referrals per detected CIN lesion).ResultsParticipation in the hrHPV-based programme was significantly lower than that in the cytology-based programme (61% vs 64%). Screen positivity and direct referral rates were significantly higher in the hrHPV-based programme (positivity rate: 5% vs 9%; referral rate: 1% vs 3%). CIN2+ detection increased from 11 to 14 per 1000 women screened. Overall, approximately 2.2 times more clinical irrelevant findings (i.e. ≤CIN1) were found in the hrHPV-based programme, compared with approximately 1·3 times more clinically relevant findings (i.e. CIN2+); this difference was mostly due to a national policy change recommending colposcopy, rather than observation, of hrHPV-positive, ASC-US/LSIL results in the hrHPV-based programme.ConclusionsThis is the first time that comprehensive results of nationwide implementation of hrHPV-based screening have been reported using high-quality data with a long follow-up. We have shown that both benefits and potential harms are higher in one screening round of a well-implemented hrHPV-based screening programme than in an established cytology-based programme. Lower participation in the new hrHPV programme may be due to factors such as invitation policy changes and the phased roll-out of the new programme. Our findings add further to evidence from trials and modelling studies on the effectiveness of hrHPV-based screening.

Trials have shown that breast cancer screening is effective in reducing breast cancer mortality and gaining life-years. The question is whether taking into account the impact of a screening programme on quality of life would lead to a less positive view. Screening may have effects on quality of life in the short run for women participating and effects in the long run as a result of the expected shift in the number of women experiencing early and advanced phases of the disease, after the initiation of the programme. In this study 4 steps have been taken: (I) published studies on quality of life and breast cancer (screening) up to 1989 have been reviewed and summarized and, based on these data, the consequences of breast cancer and treatment have been described; (2) values have been assigned to the disease and treatment phases by experts in breast cancer and public health (N = 31, response 87%); (3) these values have been inserted in the MISCAN model predicting the prevalence of disease/treatment phases with and without a 2-yearly screening programme for women aged 50-70 and multiplied by the duration of these phases; (4) analyses have been done to establish the sensitivity of the results for the values inserted. The programme of 2-yearly mammographic screening for women aged 50-70 is predicted to be 8% "less effective" (range -19.7 to +3.2%) when computing quality-adjusted life-years. We conclude that this adjustment is too small to attribute a major role to quality of life in the decision to undertake a large-scale breast cancer screening programme.

Educational level is most often used to identify social groups with increased prevalence of smoking. Other indicators of socioeconomic position (SEP) might, however, be equally or even more discriminatory. This study examined the extent to which smoking behavior is related to other socioeconomic indicators in addition to educational level. Data were derived from the European Household Panel. We selected data for 45,765 respondents aged 25-60 years from nine European countries. The association between six different SEP indicators and smoking prevalence was examined using prevalence rate ratios (RRs) estimated through log linear regression analyses. In univariate analyses, most selected SEP indicators were associated with smoking. In multivariate analyses, educational level, occupational class, accumulated wealth (measured by household assets), and housing tenure retained independent effects on smoking (RRs about 1.20). The effects observed for activity status and household income were small and insignificant in nearly all populations. In northern Europe, educational level had the greatest predictive value in the younger age groups; occupational class and housing tenure predicted most of smoking prevalence in the older age groups. The results showed a less pronounced and more varied pattern in southern Europe. Our results indicate that smoking prevalence is related not only to educational level but also to occupational class and measures of accumulated wealth (other than income). These measures should be used in addition to educational level to identify groups at increased risk for smoking.