Real-world analysis of healthcare resource utilization by patients with X-linked myotubular myopathy (XLMTM) in the United States

This study utilized a novel claims data analysis involving a comprehensive insurance claims database and artificial intelligence capabilities to quantify the disease burden of XLMTM. Results document the substantial disease burden of XLMTM, including extensive health care resources needed to care for these patients, specifically respiratory and ventilator support, tracheostomy, gastrostomy tube feeding, wheelchair use, critical and emergency care, medications for respiratory illness and infections, and hospitalizations. Caring for these patients required multispecialty involvement (pulmonology, pediatrics, neurology and critical care medicine) and high rates of multiple hospitalizations, surgical procedures, and use of assistive devices. Notably, the average number of inpatient claims per patient aged 0 to 4 and 5 to 12 were 23.2 and 23.8, respectively. Among age- and gender-matched controls in the IPM.ai claims database representing the general population, the average inpatient claims per year for patients 0 to 4 years and 5 to 12 years of age were 0.3 for both groups (Table 5). Interestingly, the number of claims increased between 2016 and 2020. It is not apparent from the data what might account for this, but the shift from ICD-9 to ICD-10 in October 2015 may have increased granularity in the later years and the new XLMTM-specific ICD-10 code and increased genetic testing in general might have contributed to improved data capture.

Table 5 Average inpatient claims per year for patients with XLMTM and the general population

These findings are largely consistent with the high disease burden associated with need for mechanical ventilation, gastrostomy tube feeding, and wheelchair requirement reflected in the limited natural history studies of XLMTM [5,6,7,8,9], including the RECENSUS retrospective chart review of 112 males with XLMTM. This is likely due, in part, to a high degree of patient overlap between the RECENSUS study cohort [5, 6] and this claims analysis data set (76 of the patient tokens in our study were also RECENSUS patients). However, the RECENSUS study focused on disease manifestations and recorded medical management and was limited by incomplete availability of data, while our all-claims analysis represents a more complete overview of all aspects of the patients’ medical care. For example, in the RECENSUS study, codes for diagnosis of hepatobiliary disease were among the most common ICD-10 codes utilized despite hepatobiliary disease not being a primary manifestation of XLMTM. Use of a certain ICD-10 code, however, does not mean the patient has the disease of interest. Physicians often refer XLMTM patients to gastroenterology for liver evaluation, using a code for liver abnormality despite the absence of overt liver disease. This finding of high use of hepatobiliary ICD-10 codes highlights an area requiring further study in light of recent reports of hepatobiliary abnormalities as an under-appreciated aspect of XLMTM, including cholestasis [14, 15], hypertransaminemia and hyperbilirubinemia with hepatopathy and cholestasis [16, 17].

Our claims analysis expands on the findings from an economic analysis by Sacks et al. showing very high medical costs and intense healthcare resource utilization associated with caring for patients with XLMTM [11]. First hospitalization between 0 and 4 years of age for 80% of patients in our study supports Sack et al.’s estimate of mean monthly per patient direct medical costs being highest in the first year of life ($74,831), with declining costs over the second, third, and fourth years of life ($23,207, $13,044, and $9,440, respectively) [11]. In addition, inpatient admissions ($69,025) accounted for the majority of the mean monthly per patient direct medical costs [11]. Both studies identified the major burden of ventilator support and ventilation management. Moreover, our study quantified the extensive use of tracheostomy, gastrostomy tube feeding, wheelchairs, occupational and physical therapy, and home care services. The Sacks et al. analysis estimated the mean monthly per patient prescription medication cost at $540 [11] and we have shown that the most common medications prescribed for these patients are medications for respiratory illnesses and infections.

The use of deidentified tokens for record matching across research consortia and between identified research databases and anonymized public databases has been growing [18], and a recent study reported 99% precision for matching among 20,002 record pairs when first name, last name, gender, and date of birth were tokenized [19]. However, as this analysis employed a novel use of artificial intelligence capabilities on both commercial and CMS payor databases, namely Medicaid claims, it has inherent limitations. Capture of open claims data relies on billing codes that may not accurately reflect the care delivered or the clinical reasoning for ordering a given test or procedure. In addition, the existing challenges of using nonspecific congenital myopathy ICD-10 codes in research on XLMTM were further complicated by the release of the new XLMTM-specific diagnosis code during the study time frame. Given the newness of this code, it will be important to validate how rigorously it is being applied, and whether care providers are limiting its use to patients with genetically confirmed diagnoses. Finally, the need to group like codes together into a code set for reporting purposes of some data limited the granularity of our analysis. Similarly, our age-group coding was structured to group events within the patients first 4 years of life in order to avoid reporting distinct patient counts fewer than four patients. However, this approach precludes looking specifically at coding for events within the first year of life, which could be useful in the setting of XLMTM research. We also saw an unexpectedly high number (n = 20) of XLMTM patients older than 35 years, 17 of whom were identified of the basis of ICD-10 code, which raises the question of whether some older males with congenital myopathy on muscle biopsy are being coded as XLMTM without the benefit of genetic testing. Thus, although at least three patients with molecular confirmation of MTM1 mutations were over the age of 35, analysis of age at diagnosis and first hospitalization (Figs. 2 and 5) should be considered in light of the possibility that some of the other 17 might reflect overuse of the XLMTM ICD-10 diagnostic code.

Due to the nature of open source databases, our findings likely underestimate the XLMTM disease burden. While the IPM.ai dataset (and others like it) represents CMS and privately insured patients, there are coverage gaps when using open source data. In particular, the available in-hospital data often include only admission and discharge data and the events happening within the hospital stay are not captured. Nonetheless, our analysis is more broadly representative of the general US population than the more idiosyncratic RECENSUS dataset, which was based on a research program from a specific patient registry.

While currently there are no disease-modifying therapies approved to treat XLMTM, several novel therapeutic strategies have shown promise in pre-clinical disease models, including tamoxifen [20], PIK3C2B inhibition [21], dynamin 2 reduction [22], and intramuscular injections of either adeno-associated virus (AAV)-shRNA or AAV-mediated gene replacement therapy (resamirigene bilparvovec) [23,24,25,26]. Our improved understanding of the unmet medical burden reflected in these claims data will enable rigorous and appropriate risk–benefit considerations as these and other therapies are developed and become available.

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