Objective This study aimed to investigate differences in the treatment of cervical cancer by tumor morphology after accounting for demographic, diagnostic, and tumor factors.
Methods Retrospective population-based observational study using linked cancer registration and treatment data from administrative data sources of women diagnosed with cervical cancer (International Classification of Diseases, Tenth Edition C53, malignant behavior) during 2009 and 2010 in England. Descriptive analyses and multinomial regression modeling have been used to consider differences in treatment by morphological subtype. For each morphological subtype, number and percentage of cases are presented by demographic, diagnostic, and tumor factors and treatment modality. Relative risk ratios are provided for each treatment modality by morphological subtype and other specified factors.
Results Forty-three percent of women were treated surgically; 36% by clinical oncology and only 8% by combination of surgery and clinical oncology. Compared with squamous cell carcinomas, both adenocarcinomas and adenosquamous carcinomas were more likely to be treated by trachelectomy, hysterectomy, radiotherapy with hysterectomy, or chemoradiotherapy with hysterectomy than by chemoradiotherapy without hysterectomy. These differences were explained mainly by a different stage distribution, but some difference remained after adjustment for other factors including stage. As clinically recommended, neuroendocrine tumors were not treated surgically. Further treatment differences were found by age, route to diagnosis, stage, and grade. Deprivation was not generally associated with treatment differences, with 1 exception that those from more deprived areas were less likely to be treated by trachelectomy.
Conclusions Important treatment differences according to tumor morphology remain after adjusting for relevant patient demographic, diagnostic, and tumor factors. In particular, the difference between the treatment of squamous cell carcinoma and adenocarcinoma is notable.
- Cervical cancer
- Multinomial regression models
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The authors declare no conflicts of interest.
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