Early identification of podocythopathies and collagenopathies reduce unnecessary medication for patients and economic burden on healthcare system

Abstract Background and Aims Despite the efforts to improve guidelines on genetic testing of podocytopathies and collagenopathies, data on the economic burden of these diseases on healthcare systems is lacking, and economic studies have been identified as an unmet need. The lack of awareness about the genetic etiology can often lead to unnecessary procedures and treatments. We recently showed that many non-genomic examinations could be avoided using a “genetic-fist” approach. The aim of this study was 1)to quantify the healthcare resource utilization, including medications, and financial burden on the Healthcare System for the diagnosis of patients affected by collagenopathies and podocytopathies from real-life data 2)to evaluate the possible savings considering an early genetic testing. Method A collaborative network of regional nephrology centers was recently established by our group. Patients referred to our tertiary hospital for genetic testing from June 2014 to December 2022 were retrospectively enrolled in the study. All patients received a diagnosis of podocytopathy or collagenopathy; the length of follow-up was considered from the onset of symptoms to the genetic testing. Direct medical costs (medication use, in-hospital visits, invasive procedures, blood sampling, imaging studies, hospital admissions, and genetic tests) were collected from clinical records. Costs were calculated based on the Regional Health Reimbursement System, including supplies, staff, results reporting and overheads and expressed in euros. The costs were compared with those of “genomic first” approach (a basic panel of examinations according to guidelines followed directly by genetic testing for the final diagnosis (exome sequencing) to be done in one year follow-up. Results The study enrolled 43 patients (23 female), 22 with a diagnosis of podocytopathy and 21 with collagenopathy. Four patients were followed-up by more than one nephrology department from different hospitals. The median length of follow-up was 3.5 years (range 1–33 years). 20 patients were treated with steroids, with 9 receiving more than one course, while others were treated with cyclosporine, tacrolimus, MMF, rituximab, cyclophosphamide, or abatacept. 11 patients received renal replacement therapy during the follow-up, and 2 underwent a renal transplant (one patient underwent two transplants). Each patient underwent a mean of 13 blood drawings and urinalysis (mean 4 times/year/patient), with 39 patients undergoing at least one imaging study, most commonly a renal ultrasound. 26 patients underwent a renal biopsy (5 needed more than one biopsy). On average, each patient needed 7 in-hospital visits (2 visits/year/patient). Each patient underwent one genetic test, mainly exome sequencing, with 4 patients undergoing Sanger and 11 undergoing a gene panel. The economic costs related to medication during the follow-up were 98,252 euros (mean 698 euros/patient/year). In-hospital visits cost 4,125 euros, while hospital admissions for biopsy cost in total 68,138 euros. Blood exams and urinalysis cost 68,926 and 2,560 euros, respectively (mean 532 and 31 euros/patient/year). Imaging studies cost 9,023 euros (mean 83.5 euros/patient/year), and genetic testing cost 146,000 euros (1,540 euros/patient/year) for exome sequencing, 21,398 euros for gene panels, and 2,216 euros for Sanger sequencing. In total, we recorded expenses of 3,897 euros per patient per year of follow-up before the diagnosis. This was almost the amount of a basic panel of exams coupled with exome sequencing (3,878 euros); however, after the first year, the early genome sequencing approach is cost-saving since other medications and non-genomic examinations can be avoided. Conclusion This study highlights the substantial amount of unnecessary treatments and examinations the patients are exposed to in unsuspected genetic diseases with consequent economic impact on the Healthcare System. Early identification of these diseases can reduce this burden. These data are important for policy makers in resource allocation.