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NAACCR / IACR Combined Annual Conference, Vancouver, Canada 9 th -13 th June 2019

NAACCR / IACR Combined Annual Conference, Vancouver, Canada 9 th -13 th June 2019. Socio-economic position and prevalence of comorbidity in cancer patients in England: a population-based study of four cancers.

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NAACCR / IACR Combined Annual Conference, Vancouver, Canada 9 th -13 th June 2019

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  1. NAACCR / IACR Combined Annual Conference, Vancouver, Canada 9th-13th June 2019 Socio-economic position and prevalence of comorbidity in cancer patients in England: a population-based study of four cancers Helen Fowler, AurelienBelot, Libby Ellis, Camille Maringe, Miguel Angel Luque-Fernandez, Edmund Njeru Njagi, Neal Navani, Diana Sarfati, Bernard Rachet

  2. Comorbidity • Existence of a long-term health condition in the presence of a primary disease of interest • Generally, more prevalent with older age and lower socio-economic position (SEP) • Less is known about prevalence of comorbidity in cancer patients • Can influence treatment and outcomes • SEP inequalities in cancer treatment and short-term mortality – due to comorbidity?

  3. Aims of study Use electronic health records to estimate comorbidity prevalence in cancer patients, in order to: • Establish prominent comorbid conditions • Identify patterns in comorbidity by SEP (adjusting for age and sex) Four cancers: Colon, rectum, lung, Hodgkin lymphoma (HL)

  4. Data England National Cancer Registry data • Patient / tumour information: • Age, sex, SEP (deprivation), type of cancer and date of diagnosis England hospital admissions records (“Hospital Episode Statistics”, HES) • Comorbidity information: • Diagnostic information, hospital admission and discharge dates

  5. Fourteen conditions considered as comorbidities Timeframe for inclusion: Condition diagnosed up to six years prior to cancer diagnosis

  6. Methods of analysis • Prevalence (percentage): crude, and adjusted for age and sex • Logistic regression: adjusted* odds ratio of a given condition being present • Multinomial logistic regression: adjusted* probability of condition being present as a single or (part of) multiple comorbidity *adjusted for age, sex and deprivation

  7. Patients: 15-90 years at diagnosis No. of patients Sex Colon Rectum Lung HL Age Deprivation group Colon Rectum Lung HL

  8. Patients: 15-90 years at diagnosis No. of patients Sex Colon Rectum Lung HL Age Deprivation group Colon Rectum Lung HL

  9. Patients: 15-90 years at diagnosis No. of patients Sex Colon Rectum Lung HL Age Deprivation group Colon Rectum Lung HL

  10. Comorbidity status by cancer type Percentage of patients with 0, 1 or 2+ comorbidities

  11. Crude and adjusted prevalence (%): colon cancer

  12. Crude and adjusted prevalence (%): lung cancer

  13. Crude and adjusted prevalence (%): HL

  14. Odds ratios of a given condition present, by deprivation group (Male colon cancer patients, aged 70 years) Deprivation group (1 = Least deprived, REF)

  15. Odds ratios of a given condition present, by deprivation group (Male colon cancer patients, aged 70 years) Deprivation group (1 = Least deprived, REF)

  16. Probability (%) of having condition as single or multiple comorbidity(Male colon cancer patients)

  17. Probability (%) of having condition as single or multiple comorbidity(Female colon cancer patients)

  18. Conclusions • Common prevalent conditions in each of the four cancers • Similar prevalence patterns by deprivation, age and sex • Deprivation was associated with almost all of 14 comorbid conditions, and with multiple comorbidity • Prevalence of some conditions may be underreported in hospital admissions data • Important insight for investigating the role of specific conditions on cancer outcomes

  19. Acknowledgments Bernard Rachet AurelienBelot Libby Ellis Camille Maringe Miguel Angel Luque-Fernandez Edmund Njeru Njagi Neal Navani Diana Sarfati Michel Coleman Thank you!

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