Appendix 5 - Variables defined for the treatment variation analysis

Treatment dates for each tumour were extracted from multiple data sources in a manner consistent with internal NDRS standard operating procedures.

Briefly, dates of systemic anti-cancer therapy administrations and major surgical resection procedures were extracted at a tumour level from the NCRD if they occurred during the primary course of therapy (defined for ovarian cancer as the period between one month prior and up to nine months following diagnosis). Where patients with tumours selected into the cohort were known to have not received another primary cancer diagnosis during the 18 months before or after the primary tumour of interest, these treatment data were supplemented by patient-level information from the Systemic Anti-Cancer Therapy (SACT) ¹and Hospital Episode Statistics (HES) Admitted Patient Care (APC) and Outpatient (OP) datasets. ²Consistent with NDRS operating procedures, SACT and HES data were not used if a patient had evidence of multiple primary cancer diagnoses within the 18 months before or after the primary tumour of interest as patient-level linkage is such that the precise tumour to which a treatment relates cannot be reliably identified.

A list of major surgical resections considered is provided in Table 22 of the data downloads section. . These are referred to as ‘surgery’ within the body of this report.

Systemic anti-cancer therapies were excluded from the analysis if they pertained exclusively to a supportive regimen, such as anti-emetic or analgesic medication for the treatment of cancer symptoms. Throughout the main body of the report, systemic anti-cancer therapy is referred to as ‘chemotherapy’.

Radiation therapy was not considered as it is rarely prescribed for ovarian cancers.

Once all relevant treatment dates were extracted by type of treatment (surgery or chemotherapy), each tumour was assigned to one of the following five groups according to the order in which treatments were delivered:

1. No surgery or chemotherapy
2. Primary surgery with adjuvant chemotherapy (i.e., surgery followed by chemotherapy)
3. Neoadjuvant chemotherapy with interval debulking surgery (i.e., chemotherapy followed by surgery)
4. Chemotherapy but no surgery
5. Primary surgery but no chemotherapy

Based on the above treatment groups, four binary comparison groups were created for use in the treatment analyses described in the main body of this report:

1. Any treatment (groups two to five) versus no treatment (group one)
2. Surgery (groups two, three and five) versus no surgery (groups one and four)
3. Chemotherapy (groups two, three and four) versus no chemotherapy (groups one and five)
4. Primary surgery with adjuvant chemotherapy (group two) versus neoadjuvant chemotherapy with interval debulking surgery (group three)

Notes:

1. Bright CJ, Lawton S, Benson S, Bomb M, Dodwell D, Henson KE, McPhail S, Miller L, Rashbass J, Turnbull A, Smittenaar R. Data Resource Profile: The Systemic Anti-Cancer Therapy (SACT) data set. Int J Epidemiol. 2020;49(1):15-15l.
2. Herbert A, Wijlaars L, Zylbersztejn A, Cromwell D, Hardelid P. Data Resource Profile: Hospital Episode Statistics Admitted Patient Care (HES APC). Int J Epidemiol. 2017;46(4):1093-1093i.

Several patient and tumour characteristics were deemed by the project team as likely to be associated with clinical decision-making. In order to help isolate the relationship between geography and treatment, analyses were adjusted for the following variables:

• Patient age at diagnosis
• Tumour morphology (the histological type of the malignancy, such as clear cell carcinoma)
• Stage at diagnosis (the size and spread of the tumour)
• Charlson comorbidity index (the burden of comorbid health conditions)
• Area deprivation

The Eastern Cooperative Oncology Group (ECOG) performance status of patients was also considered as a confounding factor. This rates the physical function of patients from 0 to 4, with a score of 4 indicating complete disability and total confinement to a bed or chair.¹However, performance status was not included in linear probability models owing to a high degree of missing data (49.7%, n=2,889; Table 7).

A Charlson comorbidity score was derived for each tumour, drawing on diagnosis data from the NCRD and HES APC datasets. Consistent with a NDRS standard operating procedure, comorbid diagnoses were selected if they occurred between three and 27 months prior to the cancer diagnosis of interest. As shown in Table 21, a total of 15 medical conditions were considered and assigned values between one and six. Comorbid conditions include myocardial infarction (heart attack), dementia and liver disease. The final index ranges from 0-25, with a higher score indicating a greater burden of comorbid disease. If a patient had no linkage to HES APC (as happens for private patients or patients with no inpatient admissions), and no evidence of another primary cancer diagnosis, a score of zero was assumed.

Area deprivation is reported in quintiles according to the Index of Multiple Deprivation 2019, which provides a relative measure of deprivation for the patient’s residence.² It is constructed using data spanning seven distinct domains, including income, employment and education. For this study, the index was defined by linking the postcode of each patient at the time of diagnosis to a 2011 Office for National Statistics (ONS) Census Lower Super Output Area (LSOA).³ Each LSOA is ranked by the ONS according to the derived level of deprivation for the geography, and then assigned to a quintile.