Poster presentation

Investigating the differences in inequalities of uterine cancer treatment before and after COVID-19 in England

Dr Jennifer Davidson presents recent research at ISPOR Europe 2022 assessing the changes in uterine cancer treatment before and after the emergence of COVID-19.

 

uterine cancer poster image

OBJECTIVES

Uterine cancer (UCa) is the most common gynecological cancer and 4th most common cancer in women. It has been well documented that the incidence rates of UCa are higher in older women, more socially deprived areas, and among women of Black ethnicity. The objective of our analysis was to describe changes in inequalities in UCa before and after COVID-19.

METHODS

Using an England-wide reimbursement secondary care dataset we identified all women diagnosed with uterine cancer. We used a binary classification of pre- (01 April 2018 to 31 March 2020) and post-COVID-19 pandemic (01 April 2020 to 31 March 2022) to group timing of diagnosis. We compared the age, ethnicity, and socioeconomic profile of the women diagnosed before and after COVID-19 using χ² tests. Socioeconomic deprivation was derived from Indices of Multiple Deprivation (IMD) quintiles. Where there is no difference of effect, 20% of the given population should be observed in each quintile.

RESULTS

There were 11,231 women in England first diagnosed with UCa between April 2018 and March 2022; 6,177 were diagnosed pre-COVID-19 pandemic and 5,054 post-COVID-19. There was no difference in the age breakdown of those diagnosed with uterine cancer pre- and post-COVID-19 (50-59 years 20.8% in both time periods. Pre-COVID-19, fewer women from the most deprived IMD quintile were diagnosed with UCa compared with the least deprived group (p-value 0.034). In the post-COVID-19 period, UCa diagnoses fell significantly among the least deprived compared with pre-COVID-19 (14.6%, vs 16.3% pre-COVID-19; p-value 0.04).

CONCLUSION

Diagnosis of uterine cancer decreased after the onset of COVID-19, likely due to reduced non-COVID-19 healthcare interactions. Prior to COVID-19, there were fewer women from the most deprived areas of England with a Uca diagnosis, this reduced further after the onset of the pandemic. This finding warrants further investigation to ensure equal access to care.

Jennifer Davidson

Dr Jennifer Davidson

Head of Research

Jennifer is Head of Research and provides epidemiological expertise into our study design and execution. She holds a Masters in Public Health Research and is currently completing her PhD in Epidemiology and has previously worked at Public Health England leading a team of epidemiologists, analysts and data managers. Jennifer has extensive experience in peer review publication, with articles published in various journals.

Caoimhe Rice

Dr Caoimhe Rice

Clinical Consultant and Health Economist

Dr. Caiomhe is an experienced health economist and is well-versed in conducting economic analyses, writing research papers and analysis plans. She is an A&E physician with nephrology specific expertise and a graduate from the University of Cambridge. Her achievements include conducting cost-effectiveness analyses for the UPSTREAM trial and writing economic chapter of the NIHR Health Technology Assessment report. Caoimhe has also developed a micro-costing strategy for calculating accounting costs of complex surgical procedures in the ROMIO oesophagectomy trial.

Sara Carvalho

Dr Sara Carvalho

Biostatistician

Dr Sara Carvalho is a biostatistician at CorEvitas holding a first-class degree in Biomedical Engineering. With broad experience in the academic environment, after concluding a PhD in Biostatistics at the University of Maastricht, she extended her set of skills within the genomics field at the Cancer Genetic Epidemiology Institute at the University of Cambridge. The recent transition into Industry has been a great challenge in which her knowledge and expertise have been used to derive meaningful information from real-world evidence data, providing statistical expertise into client research project design and execution.

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