Catastrophic costs and expenditure and referral pathways influence treatment of Breast cancer in India: (CROCODILE-B)

The aim of the study is to identify financial and non-financial barriers to comply with treatment for breast cancer in India. The study will be a mixed-methods study comprising quantitative data from up to 10 tertiary hospitals and qualitative work from interviews with patients and healthcare professionals where the outcome is the incidence of catastrophic expenditure due to out-of-pocket payments for cancer care at 3 months and 6 months and 1 year after breast cancer diagnosis. A mixed method study is being done as we are looking at identifying barriers to adherence to therapy as well as the patient’s ability to cope with the costs of treatment.

Study Setting and design: This study will be run in ten hospitals in India where cancer treatment is available and routinely delivered. This will be a prospective, multicentric, mixed-methods study with two main workstream: 1. Quantitative workstream: a prospective cohort study to determine the catastrophic expenditure 2. Qualitative workstream: to explore patient and professionals perspectives about the barriers to breast cancer treatment compliance.

The primary objective of this study is to identify the proportion of breast cancer patients suffering catastrophic expenditure due to out-of-pocket payments for cancer treatments. The secondary objectives are: 1. To assess the catastrophic expenditure rate at 3 months, 6 months and 1 year after diagnosis. 2. To identify the main drivers of treatment costs in breast cancer treatment.

Sample size: 1030 patients

Duration: 01 year 6 months

Statistical Analysis

All analyses will be conducted using the intention to treat (ITT) principle, which means that patients’ outcomes will be examined in relation to their initial treatment plan (surgery, chemotherapy, radiotherapy). Summary statistics will be supplied for all outcome measures using counts and percentages for categorical variables and means and standard deviations and/or medians and interquartile ranges for continuous variables. To test for differences across comparisons of categorical variables, the Chi square test will be utilized. Welch’s t-test or ANOVA will be used for continuous data that is parametric in character (as visually appraised). The Wilcoxon rank sum or Kruskall-Wallis tests will be employed for non-parametric data. All the analysis will be undertaken using the R studio software (v2023.12.0+369).