Effects on Cancer Prevention from the COVID-19 Pandemic

The COVID-19 pandemic led to disruption of health services around the world, including cancer services. We carried out a narrative review of the effect of the pandemic on cancer prevention services, including screening. Services were severely affected in the early months of the pandemic, and in some areas are still recovering. Large numbers of additional cancers or additional late-stage cancers have been predicted to arise over the coming years as a result of this disruption. To minimize the effects on cancer outcomes, it is necessary to return as quickly as possible to prepandemic levels of screening and prevention activity or indeed to exceed these levels. The recovery of services should address health inequalities.</p

Effects on Cancer Prevention from the COVID-19 Pandemic

The COVID-19 pandemic led to disruption of health services around the world, including cancer services. We carried out a narrative review of the effect of the pandemic on cancer prevention services, including screening. Services were severely affected in the early months of the pandemic, and in some areas are still recovering. Large numbers of additional cancers or additional late-stage cancers have been predicted to arise over the coming years as a result of this disruption. To minimize the effects on cancer outcomes, it is necessary to return as quickly as possible to prepandemic levels of screening and prevention activity or indeed to exceed these levels. The recovery of services should address health inequalities.</p

Socioeconomic inequalities in breast and cervical screening coverage in England: Are we closing the gap?

Objective:&nbsp;Health policy in the UK is committed to tackling inequalities in cancer screening participation. We examined whether socioeconomic inequalities in breast and cervical cancer screening participation in England have reduced over five years.&nbsp; Methods: Cross-sectional analyses compared cervical and breast screening coverage between 2007/8 and 2012/13 in Primary Care Trusts (PCTs) in England in relation to area-level income deprivation.&nbsp; Results: At the start and the end of this five year period, there were socioeconomic inequalities in screening coverage for breast and cervical screening. Inequalities were highest for breast screening. Over time, the coverage gap between the highest and lowest quintiles of income deprivation significantly reduced for breast screening (from 12.3 to 8.3 percentage points), but not for cervical screening (5.3 to 4.9 percentage points).&nbsp; Conclusions: Efforts to reduce screening inequalities appear to have resulted in a significant improvement in equitable delivery of breast screening, although not of cervical screening. More work is needed to understand the differences, and see whether broader lessons can be learned from the reduction of inequalities in breast screening participation

Development of PancRISK, a urine biomarker-based risk score for stratified screening of pancreatic cancer patients

© The Author(s) 2019. Published by Springer Nature on behalf of Cancer Research UK.BACKGROUND: An accurate and simple risk prediction model that would facilitate earlier detection of pancreatic adenocarcinoma (PDAC) is not available at present. In this study, we compare different algorithms of risk prediction in order to select the best one for constructing a biomarker-based risk score, PancRISK. METHODS: Three hundred and seventy-nine patients with available measurements of three urine biomarkers, (LYVE1, REG1B and TFF1) using retrospectively collected samples, as well as creatinine and age, were randomly split into training and validation sets, following stratification into cases (PDAC) and controls (healthy patients). Several machine learning algorithms were used, and their performance characteristics were compared. The latter included AUC (area under ROC curve) and sensitivity at clinically relevant specificity. RESULTS: None of the algorithms significantly outperformed all others. A logistic regression model, the easiest to interpret, was incorporated into a PancRISK score and subsequently evaluated on the whole data set. The PancRISK performance could be even further improved when CA19-9, commonly used PDAC biomarker, is added to the model. CONCLUSION: PancRISK score enables easy interpretation of the biomarker panel data and is currently being tested to confirm that it can be used for stratification of patients at risk of developing pancreatic cancer completely non-invasively, using urine samples.Peer reviewe

Overdiagnosis in breast cancer screening: the importance of length of observation period and lead time

PMCID: PMC3706885This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited