Attendance at early recall and colposcopy in routine cervical screening with human papillomavirus testing.

Attendance at early recall and colposcopy is crucial to attaining the benefits of primary high-risk human papillomavirus (HR-HPV)-based screening. Within the English HPV pilot, we analysed deprivation- and age-related patterns of attendance at colposcopy and 12- and 24-month early recall of HR-HPV positive women screened in 2013 to 2015 (N = 36 466). We fitted logistic regression models for adjusted odds ratios (OR). Despite high overall attendance, area deprivation had a small but significant impact at both early recalls, for example, attendance at 24 months was 86.3% and 83.0% in less vs more deprived areas, respectively (ORadj : 0.76; 95% CI: 0.67-0.87). Older women (≥30 years) were more likely to attend early recall than younger women (<30 years), for example, attendance at 24 months was 86.1% vs 82.3%, respectively (ORadj : 1.32, 95% CI: 1.16-1.51). Most women attended colposcopy following a baseline referral, with 96.9% attendance among more deprived and 97.8% among less deprived areas (ORadj : 0.70; 95% CI: 0.55-0.88). Differences in colposcopy attendance by deprivation level at 12 and 24 months were of approximately the same magnitude. In conclusion, attendance at early recall and colposcopy was reassuringly high. Although there were statistically significant differences by deprivation and age group, these were small in absolute terms.

Impact of screening between the ages of 60 and 64 on cumulative rates of cervical cancer to age 84y by screening history at ages 50 to 59: A population-based case-control study.

There is little empirical data on the absolute benefit of cervical screening between ages 60-64y on subsequent cancer risk. We estimate the incidence of cervical cancer up to age 84y in women with and without a cervical cytology test at age 60-64y, by screening histories aged 50-59y. The current study is a population based case-control study of women born between 1928 and 1956 and aged 60-84y between 2007 and 2018. We included all such women diagnosed with cervical cancer in England and an aged-matched random sample without cancer. Women with a hysterectomy were excluded. Exposure was cervical cytology between ages 50-64y. The main outcome was 25y cumulative risk of cervical cancer between ages 60-84y. We found that eight in every 1000 (8.40, 95%CI: 7.78 to 9.07) women without a screening test between age 50-64y develop cervical cancer between the ages of 60-84y. The risk is half: 3.46 per 1000 (95%CI: 2.75 to 4.36) among women with a test between age 60-64y but no cervical screening test at age 50-59y. The absolute difference in risk is equivalent to one fewer cancer for every 202 such women screened. The highest risk (10.01, 95%CI:6.70 to 14.95) was among women with abnormal screening at ages 50-59y and no tests 60-64y. 25y risk among women with a screening test every five years between age 50-64y was just under two in a 1000 (1.59, 95%CI:1.42 to 1.78). Results suggest the upper age of screening should be dependent on previous screening participation and results.

Epidemiology of SARS-CoV-2 during the first three waves in Scotland: a national record linkage study.

BACKGROUND: The early COVID-19 pandemic in Scotland-defined as the era before widespread access to vaccination and monoclonal antibody treatment-can be characterised into three distinct waves: March-July 2020, July 2020-April 2021 and May-August 2021. Each wave was met with various societal restrictions in an effort to reduce disease transmission and associated morbidity and mortality. Understanding the epidemiology of infections during these waves can provide valuable insights into future pandemic planning. METHODS: Scottish RT-PCR testing data reported up until 8 August 2021, the day prior to most restrictions being lifted in Scotland, were included. Demographic characteristics including age, sex and social deprivation associated with transmission, morbidity and mortality were compared across waves. A case-control analysis for each wave was then modelled to further compare risk factors associated with death over time. RESULTS: Of the 349 904 reported cases, there were 18 099, 197 251 and 134 554 in waves 1, 2 and 3, respectively. Hospitalisations, intensive care unit admissions and deaths appeared highest in wave 2, though risk factors associated with COVID-19 death remained similar across the waves. Higher deprivation and certain comorbidities were associated with higher deaths in all waves. CONCLUSIONS: Despite the higher number of cases reported in waves 2 and 3, case fatality rates were lower: likely a combination of improved detection of infections in younger age groups, introduction of social measures and vaccination. Higher social deprivation and comorbidities resulted in higher deaths for all waves.