Treatment, Resource Use and Costs Among Pediatric Patients with Neurofibromatosis Type 1 and Plexiform Neurofibromas

Patient characteristics, treatment patterns, healthcare resource utilization, and costs among patients diagnosed with neurofibromatosis type 1 with and without plexiform neurofibromas in Japan

OBJECTIVES

The objectives of this study were to retrospectively investigate the patient characteristics, treatment patterns, healthcare resource utilization (HCRU), and healthcare costs related to management of neurofibromatosis type 1 (NF1) in Japan.

METHODS

Cohorts of NF1 patients with or without plexiform neurofibromas (PN) were identified from the Medical Data Vision database in 2008-2019. Baseline characteristics, NF1 medications, HCRU, and associated costs were assessed using descriptive statistics. All-cause HCRU and costs following the first confirmed NF1 diagnosis date were analyzed per patient per year (PPPY) in Japanese Yen (JPY) and United States Dollar (USD).

RESULTS

A total of 4394 NF1 patients without PN and 370 NF1 patients with PN were identified. The mean age was 35.0 and 36.9 years, respectively. The proportion of patients with PN treated with medications was higher than that in patients without PN (except for antirheumatic/immunologic agents). Analgesics/non-steroidal anti-inflammatory drugs were the most frequently prescribed NF1 medications (44.3% and 56.0% in patients without and with PN, respectively), followed by inpatient prescriptions of opioids/opioid-like agents (17.8% and 27.6%, respectively). Inpatient admissions accounted for the highest costs in both cohorts with the average cost PPPY being JPY 2,133,277 (USD 19,861) for patients without PN and JPY 1,052,868 (USD 9802) for patients with PN.

CONCLUSIONS

NF1 is treated primarily with supportive care with analgesics/non-steroidal anti-inflammatory drugs being the most frequently prescribed NF1 medications in Japan. Findings underscored the unmet need and substantial economic burden among patients with NF1 and highlighted the need for new treatment options for patients with this disease.

The role of frailty in the clinical management of neurofibromatosis type 1: a mixed-effects modeling study using the Nationwide Readmissions Database

OBJECTIVE

Frailty embodies a state of increased medical vulnerability that is most often secondary to age-associated decline. Recent literature has highlighted the role of frailty and its association with significantly higher rates of morbidity and mortality in patients with CNS neoplasms. There is a paucity of research regarding the effects of frailty as it relates to neurocutaneous disorders, namely, neurofibromatosis type 1 (NF1). In this study, the authors evaluated the role of frailty in patients with NF1 and compared its predictive usefulness against the Elixhauser Comorbidity Index (ECI).

METHODS

Publicly available 2016–2017 data from the Nationwide Readmissions Database was used to identify patients with a diagnosis of NF1 who underwent neurosurgical resection of an intracranial tumor. Patient frailty was queried using the Johns Hopkins Adjusted Clinical Groups frailty-defining indicator. ECI scores were collected in patients for quantitative measurement of comorbidities. Propensity score matching was performed for age, sex, ECI, insurance type, and median income by zip code, which yielded 60 frail and 60 nonfrail patients. Receiver operating characteristic (ROC) curves were created for complications, including mortality, nonroutine discharge, financial costs, length of stay (LOS), and readmissions while using comorbidity indices as predictor values. The area under the curve (AUC) of each ROC served as a proxy for model performance.

RESULTS

After propensity matching of the groups, frail patients had an increased mean ± SD hospital cost ($85,441.67 ± $59,201.09) compared with nonfrail patients ($49,321.77 ± $50,705.80) (p = 0.010). Similar trends were also found in LOS between frail (23.1 ± 14.2 days) and nonfrail (10.7 ± 10.5 days) patients (p = 0.0020). For each complication of interest, ROC curves revealed that frailty scores, ECI scores, and a combination of frailty+ECI were similarly accurate predictors of variables (p > 0.05). Frailty+ECI (AUC 0.929) outperformed using only ECI for the variable of increased LOS (AUC 0.833) (p = 0.013). When considering 1-year readmission, frailty (AUC 0.642) was outperformed by both models using ECI (AUC 0.725, p = 0.039) and frailty+ECI (AUC 0.734, p = 0.038).

CONCLUSIONS

These findings suggest that frailty and ECI are useful in predicting key complications, including mortality, nonroutine discharge, readmission, LOS, and higher costs in NF1 patients undergoing intracranial tumor resection. Consideration of a patient’s frailty status is pertinent to guide appropriate inpatient management as well as resource allocation and discharge planning.

Characteristics, treatment patterns, healthcare resource use, and costs among pediatric patients diagnosed with neurofibromatosis type 1 and plexiform neurofibromas: a retrospective database analysis of a medicaid population

OBJECTIVES

The objectives of this study were to describe the characteristics and initial treatment patterns, healthcare resource use (HCRU), and costs of patients newly diagnosed with neurofibromatosis type 1 (NF1)-related plexiform neurofibromas (PN).

METHODS

This was a retrospective study of individuals enrolled in the IBM MarketScan Multi-State Medicaid database from 1 October 2014 to 31 December 2017. Patients aged ≤18 years at the index date (first diagnosis of NF1 or PN, whichever occurred later) with at least 1 ICD-10-CM diagnosis code for both NF1 and PN were included. All-cause HCRU and the associated direct costs during the follow-up period were calculated per patient per year (PPPY) in 2018 USD.

RESULTS

A total of 383 patients were included with a mean follow-up of 448 days. Most patients were diagnosed by a specialist (63.5%). During the follow-up period, pain medications were used by 58.5% of patients, 25.1% were treated with chemotherapy, 7.1% received surgery for PN, 1.6% received MEK inhibitors, and 0.8% received radiation. Mean PPPY inpatient, outpatient, ER, pharmacy, and other visits were 1.4, 17.3, 1.6, 13.6, and 25.8, respectively. Mean ± SD (median) total PPPY healthcare costs were $17,275 ± $61,903 ($2889), with total medical costs of $14,628 ± $56,203 ($2334) and pharmacy costs of $2646 ± $13,303 ($26).

CONCLUSIONS

This study showed that many pediatric patients newly diagnosed with NF1 and PN were initially treated with supportive care only, highlighting a substantial unmet medical need. This study also highlights the considerable economic burden among patients with NF1 and PN.