Use of risk-based cervical screening programs in resource-limited settings.

Cervical cancer screening and management in the U.S. has adopted a risk-based approach. However, the majority of cervical cancer cases and deaths occur in resource-limited settings, where screening and management are not widely available. We describe a conceptual model that optimizes cervical cancer screening and management in resource-limited settings by utilizing a risk-based approach. The principles of risk-based screening and management in resource limited settings include (1) ensure that the screening method effectively separates low-risk from high-risk patients; (2) directing resources to populations at the highest cancer risk; (3) screen using HPV testing via self-sampling; (4) utilize HPV genotyping to improve risk stratification and better determine who will benefit from treatment, and (5) automated visual evaluation with artificial intelligence may further improve risk stratification. Risk-based screening and management in resource limited settings can optimize prevention by focusing triage and treatment resources on the highest risk patients while minimizing interventions in lower risk patients.

Comparison of accuracy and reproducibility of colposcopic impression based on a single image versus a two-minute time series of colposcopic images.

OBJECTIVE: Colposcopy is an important part of cervical screening/management programs. Colposcopic appearance is often classified, for teaching and telemedicine, based on static images that do not reveal the dynamics of acetowhitening. We compared the accuracy and reproducibility of colposcopic impression based on a single image at one minute after application of acetic acid versus a time-series of 17 sequential images over two minutes. METHODS: Approximately 5000 colposcopic examinations conducted with the DYSIS colposcopic system were divided into 10 random sets, each assigned to a separate expert colposcopist. Colposcopists first classified single two-dimensional images at one minute and then a time-series of 17 sequential images as 'normal,' 'indeterminate,' 'high grade,' or 'cancer'. Ratings were compared to histologic diagnoses. Additionally, 5 colposcopists reviewed a subset of 200 single images and 200 time series to estimate intra- and inter-rater reliability. RESULTS: Of 4640 patients with adequate images, only 24.4% were correctly categorized by single image visual assessment (11% of 64 cancers; 31% of 605 CIN3; 22.4% of 558 CIN2; 23.9% of 3412 < CIN2). Individual colposcopist accuracy was low; Youden indices (sensitivity plus specificity minus one) ranged from 0.07 to 0.24. Use of the time-series increased the proportion of images classified as normal, regardless of histology. Intra-rater reliability was substantial (weighted kappa = 0.64); inter-rater reliability was fair ( weighted kappa = 0.26). CONCLUSION: Substantial variation exists in visual assessment of colposcopic images, even when a 17-image time series showing the two-minute process of acetowhitening is presented. We are currently evaluating whether deep-learning image evaluation can assist classification.

Low rates of HPV vaccination and cervical cancer screening: Challenges and opportunities in the context of the COVID-19 pandemic.

This invited commentary discusses the article by Richards et al. describing differences in rates of on-time HPV vaccination and cervical cancer screening in 2018 among enrollees in different insurance plans. The commentary focuses on the larger problem of low vaccination HPV rates and decreasing cervical cancer screening rates seen across all sectors. We outline challenges posed by the COVID-19 pandemic on HPV vaccination and cervical cancer screening, and discuss opportunities to improve cervical cancer prevention.

Inflammation as a predictor for delayed cerebral ischemia after aneurysmal subarachnoid haemorrhage.

BACKGROUND: The mechanism of development of delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage (SAH) is poorly understood. Inflammatory processes are implicated in the development of ischemic stroke and may also predispose to the development of DCI following SAH. The objective of this study was to test whether concentrations of circulating inflammatory markers (C-reactive protein (CRP), interleukin-6 (IL-6) and interleukin 1 receptor antagonist (IL-1Ra)) were predictive for DCI following SAH. Secondary analyses considered white cell count (WCC) and erythrocyte sedimentation rate (ESR). METHODS: This was a single-center case-control study nested within a prospective cohort. Plasma inflammatory markers were measured in patients up to 15 days after SAH (initial, peak, average, final and rate of change to final). Cases were defined as those developing DCI. Inflammatory markers were compared between cases and randomly selected matched controls. RESULTS: Among the 179 participants there were 46 cases of DCI (26%). In primary analyses the rate of change of IL-6 was associated with DCI (OR 2.3 (95% CI 1.1 to 5.0); p=0.03). The final value and rate of change of WCC were associated with DCI (OR 1.2 (95% CI 1.0 to 1.3) and OR 1.3 (95% CI 1.0 to 1.6), respectively). High values of ESR were associated with DCI (OR 2.4 (95% CI 1.3 to 4.6) initial; OR 2.3 (95% CI 1.3 to 4.2) average; OR 2.1 (95% CI 1.1 to 3.9) peak; and OR 2.0 (95% CI 1.2 to 3.3) final value). CONCLUSIONS: Leucocytosis and change in IL-6 prior to DCI reflect impending cerebral ischemia. The time-independent association of ESR with DCI after SAH may identify this as a risk factor. These data suggest that systemic inflammatory mechanisms may increase the susceptibility to the development of DCI after SAH.