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. 2022 May;42(5):486-489.
doi: 10.1002/cac2.12265. Epub 2022 Feb 7.

Colorectal cancer risk following appendectomy: a pooled analysis of three large prospective cohort studies

Joseph A Rothwell  1 , Nagisa Mori  2 , Fanny Artaud  1 , Agnès Fournier  1 , Marco Conte  1 , Marie-Christine Boutron-Ruault  1 , Simon S M Chan  3   4 , Marc J Gunter  2 , Neil Murphy  2 , Gianluca Severi  1   5
Affiliations

Colorectal cancer risk following appendectomy: a pooled analysis of three large prospective cohort studies

Joseph A Rothwell et al. Cancer Commun (Lond). 2022 May.
No abstract available

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Conflict of interest statement

The authors declare there are no conflicts of interest.

Figures

FIGURE 1
FIGURE 1
Random‐effects meta‐analyses for associations between prior appendectomy and colorectal cancer risk by tumor subsite and sex. EPIC, European Prospective Investigation into Cancer and Nutrition. The I2 statistic for heterogeneity across cohorts and the corresponding P values are given. Estimates shown are pooled HR and 95% CI derived from Cox proportional hazard models performed in each individual cohort by random‐effects meta‐analyses. HR > 1 represents an increased risk of cancer for participants with appendectomy. Harmonized multivariable models were adjusted for body mass index (kg/m2, continuous), physical activity (metabolic equivalent of task [MET] hours/week, categorical), height (cm, continuous), smoking status (current/former/never/unknown), and highest educational level (none or primary school/secondary school/technical or professional qualification/further education). In the UK Biobank dataset, history of cancer in first‐degree relatives was additionally included in models and, in the E3N dataset, the colorectal cancer screening period (before/after 2002). In the E3N dataset, BMI, physical activity, smoking status, and history of colorectal cancer in first‐degree relatives were modeled as time‐varying. In the UK Biobank dataset, models were stratified by age at recruitment, Townsend deprivation index quintiles, and assessment center region. In the EPIC dataset, models were stratified by age at recruitment and center, and stratification variables were not used for the E3N models.
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References

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