The cancer screening rate declined 39% during the COVID pandemic, according to a French study published on 2 January in Nature Cancer.
A team led by Richa Shaw, PhD, of the International Agency for Research on Cancer in Lyon, conducted a literature review to investigate the global scale and impact of COVID pandemic-related delays and disruptions on cancer services, including diagnosis, diagnostic procedures, screening, treatment, and supportive and palliative care. The review included 245 articles from 46 countries.
The group found the following regarding the effects of the COVID-19 pandemic:
- Cancer screening participation decreased by 39%.
- Diagnoses decreased by 23%.
- Diagnostic procedures decreased by 24%.
- Disease treatment decreased by 28% -- ranging from a 15% decline for radiotherapy to a 35% decline for systemic treatment during the pandemic compared with the prepandemic period.
- Medium-human development index (HDI) category countries experienced greater reductions than high- and very-high-HDI countries. (The HDI is a summary measure of average achievement in key facets of human development, including a long and healthy life, being knowledgeable, and having a decent standard of living.)
"Missing data from low-HDI countries emphasize the need for increased investments in cancer surveillance and research in these settings," the group concluded.
The full report can be found here.
![Overview of the study design. (A) The fully automated deep learning framework was developed to estimate body composition (BC) (defined as subcutaneous adipose tissue [SAT] in liters; visceral adipose tissue [VAT] in liters; skeletal muscle [SM] in liters; SM fat fraction [SMFF] as a percentage; and intramuscular adipose tissue [IMAT] in deciliters) from MRI. The fully automated framework comprised one model (model 1) to quantify different BC measures (SAT, VAT, SM, SMFF, and IMAT) as three-dimensional (3D) measures from whole-body MRI scans. The second model (model 2) was trained to identify standardized anatomic landmarks along the craniocaudal body axis (z coordinate field), which allowed for subdividing the whole-body measures into different subregions typically examined on clinical routine MRI scans (chest, abdomen, and pelvis). (B) BC was quantified from whole-body MRI in over 66,000 individuals from two large population-based cohort studies, the UK Biobank (UKB) (36,317 individuals) and the German National Cohort (NAKO) (30,291 individuals). Bar graphs show age distribution by sex and cohort. BMI = body mass index. (C) After the performance assessment of the fully automated framework, the change in BC measures, distributions, and profiles across age decades were investigated. Age-, sex-, and height-adjusted body composition reference curves were calculated and made publicly available in a web-based z-score calculator (https://circ-ml.github.io).](https://img.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/05/body-comp.XgAjTfPj1W.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
