Abstract
Objective
To evaluate the effects of metreleptin in distinct subgroups of patients with generalized lipodystrophy (GL) and partial lipodystrophy (PL), using multivariate linear regression modeling to account for the role of patients’ baseline usage of concomitant glucose and lipid-lowering medications and other covariates on their outcomes.
Materials and methods
A post-hoc statistical analysis of two published single-arm, interventional, phase 2 clinical trials at NIH was conducted. Concomitant medication use was assessed for the clinical trial population using prescription fill data, measured at baseline and the post-one year following metreleptin initiation. Pre-specified co-primary efficacy endpoints measured were change from baseline in HbA1c at month 12, and the percent change from baseline in fasting serum triglycerides (TG) at month 12. Descriptive and statistical analyses were conducted for the overall population, the separate populations with GL and PL, and additional PL subgroups defined by baseline metabolic markers of elevated HbA1c and elevated fasting TG.
Results
As previously reported, improvement in HbA1c and fasting TG from baseline to 12 months on metreleptin were observed in the overall population (mean change −1.57 percentage points and median change −37.9%, respectively) and subgroups. For both HbA1c and TG, baseline levels were significant predictors of changes after metreleptin. After considering baseline characteristics such as disease type, age, sex, and baseline HbA1c, baseline insulin use was not found to be a significant predictor of HbA1c improvement following metreleptin initiation. Similar results were seen for TG levels, with the use of any lipid-lowering medications at baseline not found to be a significant predictor of reductions in fasting TG levels.
Conclusions
Patients treated with metreleptin experienced statistically significant improvement in metabolic markers of glycemic and hypertriglyceridemic control—e.g. HbA1c and triglyceride levels—across various subgroups after controlling for baseline characteristics and concomitant medication usage.
Introduction
Lipodystrophy syndromes are rare and heterogeneous leptin deficiency and body fat disorders, associated with increased mortality and a range of comorbiditiesCitation1–4. The general or partial lack of normal fat deposits can result in metabolic symptoms, specifically insulin resistance, diabetes mellitus, and hypertriglyceridemiaCitation1,Citation5. Lipodystrophy syndromes may lead to the deficiency of nearly all adipose tissue (generalized lipodystrophy, GL), or only select adipose depots (partial lipodystrophy, PL)Citation1.
Metreleptin is a subcutaneous injection indicated as an adjunct to diet as a replacement therapy for the management of lipodystrophyCitation6. The value of metreleptin was established in a single-arm clinical trial, which achieved its co-primary efficacy endpoints of the actual change from baseline in HbA1c at month 12 and the percent change from baseline in fasting serum triglycerides (TGs) at months 12Citation7,Citation8. The regulatory trial provides a comprehensive, long-term assessment of patients treated with metreleptin, spanning 14 years of data collection, with a mean duration of treatment with metreleptin of 5 yearsCitation7. At the time of publication, metreleptin is approved for the management of metabolic complications associated with lipodystrophy in patients with GL (US, EU, Japan) and PL (EU and Japan)Citation9,Citation10.
Brown et al. 2018 reported the efficacy and safety trial outcomes for patients with GL. The mean (SD) daily dose of metreleptin in the group of GL patients was 5.0 (3.0) mg (range, 0.8–19.0 mg) and a weighted mean (SD) dose of 0.098 (0.04) mg/kg (range, 0.025–0.21 mg/kg). At baseline, GL patients had mean (SD) fasting leptin values (ng/mL) of 1.3 (1.0). The authors concluded that long-term treatment with metreleptin was well tolerated, citing significant mean reductions from baseline at month 12 for HbA1c (–2.2%) and significant mean percent change in fasting TGs (–32.1%)Citation7. Oral et al. 2019 evaluated efficacy and safety outcomes for the PL trial population, with an additional focus on patients with increased metabolic comorbidities, defined as patients with PL and baseline HbA1c ≥ 6.5% or fasting TG ≥ 500 mg/dL (PL Subgroup 1) and patients with PL and baseline HbA1c ≥ 8.0% or fasting TG ≥ 500 mg/dL (PL Subgroup 2)Citation8. The weighted mean (SD) daily dose of metreleptin in the overall PL population and PL Subgroup 1 was 0.123 (0.030) mg/kg/day (equivalent to 8.4 [2.5] mg/day) and 0.124 (0.030) mg/kg/day (equivalent to 8.4 [2.4] mg/day), respectively. At baseline, the mean (SD) fasting leptin values (ng/mL) in the overall PL group was 6.4 (3.5), in PL Subgroup 1 was 6.7 (3.7), and in PL Subgroup 2 was 6.5 (3.9). This publication found statistically significant and clinically meaningful improvements in HbA1c and fasting TG in both subgroups that were more marked in subgroup 2, indicating the potential benefit of metreleptin for specific subgroups of patients with PL.
Traditional antidiabetic and lipid-lowering medications have limited effectiveness in patients with lipodystrophyCitation1,Citation11. However, because metreleptin trials did not dictate that subjects be optimized on stable doses of available treatments for metabolic complications (insulin and other non-insulin antidiabetics for hyperglycemia, lipid-lowering agents for hypertriglyceridemia), it is not certain that the outcomes observed with metreleptin are independent of benefits available from optimal use of standard-of-care therapies. In addition, the heterogeneity of both the etiology and metabolic complications of lipodystrophy, particularly in patients with PL, means that the effects of metreleptin and its relationship to use of standard therapies could vary depending on the population considered.
Existing post-hoc analysis of patients enrolled in metreleptin trials suggests that patients with relevant metabolic abnormalities (hyperglycemia, hypertriglyceridemia) were more likely to be treated with standard medications before metreleptin and were more likely to show improved metabolic markers following metreleptin initiationCitation7,Citation8. Therefore, with the known confounding effect of more severe metabolic parameters at baseline leading to concomitant medication use, additional statistical analyses of the available data are needed to disentangle the two effects. Furthermore, subgroup analyses of patients with particular baseline characteristics can also help demonstrate the outcomes associated with metreleptin and the role of baseline concomitant medications in those specific subgroups.
The objective of this analysis is to apply multivariate linear regression modeling to evaluate the effects of metreleptin in distinct subgroups of patients with lipodystrophy while accounting for the role of patients’ usage of baseline concomitant medications and other covariates may have on their outcomes. The study begins by describing use of standard treatment for the overall lipodystrophy population and by specific subgroups at baseline, along with changes in medication use post-one year following metreleptin initiation–measured after the 12-month study visit when adjustments in concomitant medications were no longer restricted per study protocol. Co-primary efficacy endpoints are additionally presented for patient subgroups stratified by baseline medication use. Finally, regression analyses are utilized to analyze the relationship between baseline metabolic parameters, baseline concomitant medication use, and metreleptin use on metabolic parameters after 12 months of treatment.
Materials and methods
This was a post-hoc statistical analysis of two published clinical trials conducted at NIHCitation7,Citation8,Citation12.
Data source and population
Clinical trial NCT00005905 and follow-up study NCT00025883 prospectively enrolled patients from 2000 to 2014Citation7,Citation8,Citation12. Both trials were single-arm, interventional, phase 2 studies conducted at NIH to evaluate the safety and effectiveness of leptin replacement therapy with metreleptin in patients with lipodystrophy. Trial participants were aged ≥ 6 months, had clinically-significant lipodystrophy, circulating leptin levels < 12.0 ng/mL in females and < 8.0 ng/mL in males, and one or more metabolic abnormalities including diabetes mellitus defined per American Diabetes Association criteria, insulin resistance (fasting insulin > 30 μU/mL [215 pmol/L]), or hypertriglyceridemia (fasting triglyceride > 200 mg/dL)Citation13,Citation14. The clinical trial protocols did not require that concomitant medications be optimized to the standard of care prior to initiating treatment. Designation of generalized and partial lipodystrophy was made at enrollment of the primary trial. Vital signs, laboratory assessments, anthropometric and metabolic measures, measures of vital organ function, metreleptin use, and medical history were recorded at baseline and scheduled post-baseline visits. Clinical values were collected at baseline and during follow-up visits at 1, 2, 4, 6, 8 and 12 months after therapy startCitation7,Citation8,Citation12. While the trial protocol did not restrict patient inclusion based on the use of select other medications (non-metreleptin), only limited changes in medications (specifically changes in medication dose to prevent hypoglycemia) were permitted through the immediate 12 months post metreleptin initiation.
Among the 107 enrolled clinical trial patients, 102 were included in the full analytic set (FAS) population. The FAS population was defined as all patients who had either primary efficacy parameter of interest measured at baseline and at least one post-baseline visit. Within the FAS population, one patient was withdrawn from the study due to unique clinical circumstances associated with pancreatitis shortly prior to metreleptin initiation, including nonadherence to study drug administration and a > 1000% increase from baseline to month 12 in fasting TG levels; this patient was excluded from the present analysis. Therefore, the full population for this analysis included 101 patients. Additional subgroup analyses explored the following populations: Patients with GL (n = 62); patients with PL (n = 39); patients with PL and baseline HbA1c ≥ 6.5% or fasting TG ≥ 500 mg/dL (PL Subgroup 1, n = 29); patients with PL and baseline HbA1c ≥ 8.0% or fasting TG ≥ 500 mg/dL (PL Subgroup 2, n = 21).
Medication usage metrics
Baseline concomitant medication use was evaluated at screening for the clinical trial population, while subsequent concomitant medication use was assessed using prescription fill data that was extracted retrospectively from medical records maintained at the primary trial site. Medication data included information on start and end dates of a product, an identifier of ‘ongoing’ medication status, and several other indicators to classify medications across different product types. In particular, medication classes relevant to lipodystrophy and related conditions such as antidiabetic medications (insulin and others) and lipid-lowering medications such as fibrates, statins and others were the focus of the analysis. Other medications with potential metabolic effects (e.g. some antihypertensive and/or psychoactive drugs) could not be systematically analyzed in this post-hoc analysis. Concomitant medication adherence and changes in drug potency within classes of medications were not tracked.
This analysis assessed concomitant medication use at baseline, post-one year following metreleptin initiation, and at the end of the full trial follow-up period. Baseline medications included all fills with a start date on or before metreleptin initiation and an end date on or after metreleptin initiation. Fills with missing end dates were imputed based on any indication of ‘ongoing’ status, or other available month or year information.
Medication use at the post-one year time point included all medication fills having a start date on or before and an end date on or after 14 months following metreleptin treatment initiation. Given that limited changes in medication (specifically dose adjustments to prevent hypoglycemia) were permitted through the immediate 12 months following metreleptin initiation, the 14-month mark allowed for a non-restrictive point of assessment of medication use when patients may have adjusted their treatment patterns. If a patient had no identified medication use at the post-one year time point based on this definition, they were deemed to have discontinued concomitant medication products. Patients may have discontinued use by the post-one year time point but resumed usage on a future date; this was not assessed in the current analysis.
In the antidiabetic category, overall medication changes were assessed between baseline and the post-one year following metreleptin initiation, specifically tracking the presence or absence of insulin use over time. For the lipid-lowering category, changes in the number of therapies were assessed.
Statistical analyses
The prespecified co-primary efficacy endpoints for the clinical trial were the change from baseline in HbA1c at month 12, and the percent change from baseline in fasting TGs at month 12. The last observation carried forward (LOCF) method was specified for imputation of any missing month 12 results and required that the results occur at least 6 months (180 d) post-baseline. Thus, analysis of primary efficacy endpoints was to include all patients that had baseline and at least Day 180 measurements, but included slightly fewer patients than the FAS population.
Descriptive statistics were presented for the overall lipodystrophy population, patients with GL, patients with PL, patients in PL subgroup 1, and patients in PL subgroup 2. Continuous variables were summarized as mean (standard deviation) or median (IQR), and categorical variables were summarized as n (%). Co-primary efficacy endpoints were stratified by baseline medication use. Additional laboratory outcomes including alanine aminotransferase (ALT), aspartate aminotransferase (AST), and urine albumin were described at 12 months stratified by baseline insulin use, and without stratification at 36 months.
Multivariate linear regression models were used to evaluate the relationship between baseline concomitant medication usage and metabolic outcomes, after controlling for additional factors, such as baseline laboratory values and patient characteristics. For the linear regression analysis of fasting TG levels, we evaluated the difference in log-scaled baseline values to log-scaled 12 month values and therefore, the outcome is interpreted as the predicted percent decline in fasting TG levels. Regression analyses were stratified by subgroup.
Analyses were conducted using SAS 9.4 (Cary, NC).
Results
Patient characteristics
Data from 101 trial patients (62 GL, 39 PL) were part of this post-hoc analysis. The average age of the full population was 23.6 years (SD: 15.5 years) at the start of metreleptin treatment, but the average patient with PL was over twice the age of the average patient with GL [34.2 years (SD: 15.0 years) vs 17.0 years (SD: 11.6 years); ]. Most patients (85 of 101 patients, 84.2%) were female and had been previously diagnosed with diabetes and hypertriglyceridemia. Across all 101 patients, the average baseline HbA1c level was 8.3% (SD: 2.3%), the median baseline fasting TG level was 405 mg/dL (IQR: 221–876 mg/dL), and the average C-peptide level was 4.58 ug/L (SD: 3.4 ug/L). Patients with GL had higher average C-peptide levels at baseline (5.22 ug/L, SD: 4.1 ug/L) compared with patients with PL (3.75 ug/L, SD: 2.2 ug/L). Patients in PL Subgroup 2 had the highest average baseline HbA1c level (9.4%, SD: 1.9%) and highest median baseline fasting TG level (795 mg/dL, IQR: 263–1377 mg/dL).
Table 1. Baseline characteristics.
The majority of patients were taking an antidiabetic medication at baseline in the full population (83.2%), with all but one patient who met the criteria for both PL subgroups taking an anti-diabetic medication at baseline. Approximately half of all patients were taking insulin at baseline. In addition, lipid-lowering medications were commonly used at baseline, ranging from 50% of all patients with GL to 90.5% of patients in PL Subgroup 2.
Concomitant medication usage
Antidiabetic medications
Among the 49 patients with GL taking an antidiabetic medication at baseline (), 35 were taking insulin, either alone or with another antidiabetic. The remaining 14 patients were taking one or more other antidiabetic products. Among the 17 patients not on antidiabetic therapy at baseline, 6 had a diagnosis of diabetes. Slightly more than half of all patients with insulin use at baseline were able to discontinue insulin use, and only one patient with GL introduced insulin to their treatment regimen by the post-one year time point.
Table 2. Antidiabetic medication change relative to baseline.
Seventeen of the 39 patients with PL were taking insulin at baseline, while 18 were taking a non-insulin antidiabetic product. By the post-one year time point, no patients with PL had discontinued insulin treatment, and 3 patients supplemented their antidiabetic regimen with insulin.
Other antidiabetic medications included alpha glucosidase inhibitors, biguanides, sulfonylureas, thiazolidinediones, dipeptidyl peptidase 4 (DPP-4) inhibitors, and combinations of oral blood glucose lowering drugs.
Lipid-lowering medications
Lipid-lowering medications () were categorized into the following classes − 1) fibrates; 2) statins; 3) fish oil; 4) bile acid sequestrant; 5) nicotinic acid. Patients could be on any combination of these products at baseline or at follow-up, and the number of therapies at the level of these classes was analyzed. 31 out of 62 patients with GL and 34 out of 39 patients with PL had some form of concomitant lipid-lowering medication use at baseline, with close to half of them on monotherapy (n = 15 for GL; n = 22 for PL).
Table 3. Lipid-lowering medication change relative to baseline.
Across both GL and PL categories, most patients maintained the same number of lipid-lowering therapies at the post-one year time point (GL: 48, PL: 32). 13 patients with GL were able to reduce the number of therapies, and only 1 patient added a therapy by the post-one year time point. Five patients with PL increased the number of therapies, all adding to a monotherapy regimen (n = 5), while 2 patients with baseline lipid-lowering medication reduced the number of therapies by the post-one year time point.
Primary endpoints by concomitant medication usage
Of the 101 patients in the full population, 95 had both baseline and 12 month HbA1c levels and 93 had both baseline and 12 month fasting TG levels available. The evaluable population and subgroups (GL, PL, PL Subgroup 1, PL Subgroup 2) all demonstrated improvement in HbA1c and fasting TG levels from baseline to 12 months on metreleptin. Patients with PL had smaller reductions in both HbA1c and fasting TG levels compared to patients with GL. However, the magnitude of the decline differed between patients with and without baseline concomitant medication usage (). Without considering any confounding factors, patients with GL with baseline insulin usage had higher HbA1c at baseline and greater reductions in HbA1c following metreleptin initiation. The opposite relationship was observed in patients with PL, such that those with baseline insulin use had a smaller decrease in HbA1c at 12 months as compared to those without baseline insulin. Patients with GL, patients with PL, and patients in both PL subgroup 1 and PL subgroup 2 with baseline lipid-lowering medication usage had higher median baseline fasting TG levels and greater reductions in fasting TG levels.
Table 4. Primary endpoints, with or without concomitant medication usagea.
We developed a multivariate linear regression model for each subgroup predicting the absolute change in HbA1c levels from baseline to 12 months, where a negative value was indicative of improvement. As shown in , patients on average experienced a −1.57 percentage point change in HbA1c at 12 months (GL, −2.16 percentage points; PL, −0.61 percentage points). After considering baseline characteristics such as disease type, age, baseline HbA1c levels and sex, baseline medication usage was not a significant predictor of HbA1c improvement. Inclusion of baseline HbA1c values as controls in the regressions was necessary due to the high correlation between baseline HbA1c values and other patient characteristics, including use of concomitant medications. Baseline HbA1c values were significantly associated with metreleptin improvement; for every 1 point increase in baseline HbA1c level, patients with GL treated with metreleptin experienced on average a 0.75 percentage point decline in HbA1c by month 12 () and patients with PL experienced a 0.35 percentage point decline. Specifically, the regression analysis showed that the substantially larger decrease in 12 month HbA1c among the insulin-treated GL group (–2.87) compared to the GL group not receiving insulin at baseline (–1.18) was due to differences in baseline HbA1c (9.90 vs. 6.81) rather than differences in insulin use. In a sensitivity analysis, the inclusion of baseline use of lipid-lowering medications as a covariate in the model did not meaningfully affect the results (Supplementary Table 1).
Table 5. Multivariate regression of absolute change in HbA1c levels – stratified modelsa.
In the trial, patients experienced a median −37.9% change in fasting TG levels after 12 months of metreleptin, including −53.3% among patients with GL and −28.7% among patients with PL. After accounting for baseline attributes including disease type, age, baseline TG, sex (where applicable), and baseline use of lipid-lowering medications, regression analysis yielded similar estimates for median percent change in fasting TG levels by 12 months: GL, −48.2%; PL, −28.1%; PL Subgroup 1, −46.6%; and PL Subgroup 2, −52.7%. Baseline fasting TG level was a significant predictor of the reduction observed with metreleptin treatment (p < .0001 for patients with GL, patients with PL; p < .005 for PL Subgroup 1; p < .01 for PL Subgroup 2; ). Usage of lipid-lowering medications at baseline was not a significant predictor of reductions in fasting TG levels (p > .10 for patients with GL, patients with PL, and patients in both PL Subgroup 1 and PL Subgroup 2). In a sensitivity analysis, the inclusion of baseline use of insulin as a covariate in the model did not meaningfully affect the results (Supplementary Table 2).
Table 6. Multivariate regression of absolute change in log(triglyceride) levels – stratified models (GL and PL)a,b.
Additional laboratory outcomes
Patients treated with metreleptin exhibited improvements across multiple laboratory metrics beyond the primary endpoints of HbA1c and fasting TG levels at 12 months (). Patients with GL and those with PL both experienced significant reductions in AST levels, while patients with GL and those in PL Subgroups 1 and 2 experienced significant reductions in ALT. Overall, patients in the PL Subgroup 1 showed similar benefit from metreleptin treatment as those in PL Subgroup 2. In particular, the absolute change from baseline to 12 months was statistically significant (p < .05) for ALT and AST levels in both PL subgroups. For those labs showing significant improvement, the absolute change was similar between both PL subgroups. Consistent with findings from the primary endpoints of interest, among patients with PL and those in PL Subgroups 1 and 2, those with baseline insulin use experienced greater reductions in ALT, AST, and urine albumin levels.
Table 7. 12 Month laboratory outcomes stratified by baseline insulin usage.
The improvement in laboratory values was largely sustained at 36 months for those patients with evaluable data (). Glucose, ALT, and AST were significantly reduced in both patients with GL and those with PL, despite the smaller sample size available for evaluation. PL Subgroup 1 and PL Subgroup 2 exhibited improvements in all laboratory values when comparing 36 months to baseline.
Table 8. 36 Month laboratory outcomesa.
Discussion
In this analysis of the influence of baseline concomitant medication use on metabolic changes after metreleptin, we found that patients with lipodystrophy taking a concomitant medication for diabetes or hypertriglyceridemia at baseline had higher baseline HbA1c and triglycerides. This observation of higher baseline laboratory values among concomitant medication users suggests that the current standard of care was not adequately controlling their disease. We observed the expected relationship between baseline elevations in HbA1c and triglycerides, and improvements in these parameters after metreleptin, such that patients with the highest values at baseline experienced the greatest reductions after treatment. Because poorly controlled metabolic disease at baseline was associated with concomitant medication use, the relationship between concomitant medication use and improvement in metabolic laboratory markers was confounded by baseline levels. The results of our regression models showed that, 12 months after initiation of metreleptin, there was significant improvement in metabolic control after controlling for baseline concomitant medications. These improvements were observed across all subgroups.
In contrast to prior analyses of this dataset, this analysis measured medication use at 14 months, after the 12-month study visit and thus after restrictions in the trial protocol regarding medication changes were liftedCitation7,Citation8,Citation15. By examining medication use at this time point, this analysis captured clinically indicated changes in medications other than metreleptin that were considered necessary in light of the patients’ clinical status after one year of metreleptin treatment. The observation that medications remained stable or were reduced for most study participants is consistent with metreleptin having a role in controlling metabolic manifestations of lipodystrophy.
This analysis demonstrates the potential benefit metreleptin may offer to patients with GL, as well as specific subgroups of patients with PL. Of interest, the relationship between baseline concomitant insulin use and lowering of HbA1c differed in patients with GL and PL. Patients with PL were older at the time of metreleptin treatment, and may have had reduced beta cell functioning compared to patients with GL as evidenced by the lower average baseline C-peptide values in patients with PL compared to patients with GL. We thus hypothesize that insulin use may be an indicator of beta-cell failure in PL, whereas it may be an indicator of more severe insulin resistance in GL. It has been previously shown that, while metreleptin mitigates insulin resistanceCitation16, it does not improve beta cell functionCitation17. Thus, metreleptin might be expected to improve HbA1c in patients with preserved beta cell function, but not in those with beta cell failure. Patients with PL and more severe metabolic complications also experienced statistically significant improvements in clinically relevant laboratory metrics outside the primary efficacy endpoints, including ALT and AST levels. These results suggest that metreleptin can provide clinical benefit to patients with baseline HbA1c ≥ 6.5% or fasting TG ≥ 500 mg/dL.
Despite the range of antidiabetic products available today, the patients in this analysis had limited variety in medications. Some classes of antidiabetic products available today, such as GLP-1 analogs, SGLT-2 inhibitors, and DPP-4 inhibitors, were not approved during the earlier patients’ follow-up period. In addition, a large proportion of the patients enrolled were pediatric and therefore only metformin and insulin were FDA-approved given their age. Antidiabetic concomitant medication use, while common in the trial, was thus less heterogeneous than one might expect because of the trial duration and younger study population. Thus, in this analysis, non-insulin antidiabetic products (including alpha glucosidase inhibitors, biguanides, sulfonylureas, thiazolidinediones, dipeptidyl peptidase 4 inhibitors, and other combinations of oral blood glucose-lowering drugs) were analyzed together as one category as noted in .
While this analysis relied on data previously publishedCitation7,Citation8,Citation12, there are some limitations. First, this is a post-hoc analysis and thus was not prespecified prior to the original collection of patient data. The primary trial was an uncontrolled, prospective, non-randomized, open-label trial of metreleptin in lipodystrophy. In addition, concomitant medications data were not collected in the primary trial data set but were recorded concurrently in medical records maintained at the primary trial site for each patient. Concomitant medication data used in this analysis were extracted from this source and combined with trial data on the primary outcomes. Accuracy and completeness of the medications data may therefore be lower than for the primary outcomes. However, these limitations are not suspected to bias the results in one direction. Changes to dosage and frequency were not recorded consistently for the full analysis population, and therefore only the discontinuation or addition of medications was evaluated, not potential changes in dose from baseline.
Conclusion
Patients treated with metreleptin experienced statistically significant improvement in metabolic parameters across various subgroups (GL, PL, PL with severe metabolic complications) after controlling for baseline concomitant medication usage. These findings are also consistent with other research that found metreleptin led to statistically significant improvement in prevalent comorbidities in patients with lipodystrophyCitation18.
Transparency
Declaration of funding
This study was funded by Amryt Pharmaceuticals and Aegerion Pharmaceuticals, a wholly-owned subsidiary of Amryt.
Declaration of financial/other relationships
ECarr and FC are employees of Amryt and owns stock/stock options. KA, KC, DG, EM and ET are employees of Analysis Group Inc., which has received consultancy fees from Amryt and Aegerion, a wholly-owned subsidiary of Amryt. Metreleptin for the clinical trials conducted at NIH was donated by Amgen Pharmaceuticals, Amylin Pharmaceuticals, and Bristol Myers Squibb/Astra Zeneca. Aegerion Pharmaceuticals provided subsequent support in analyzing data from the clinical trials. Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.
Authors’ contributions
ECarr, ET, KA and KC conceptualized the study. KA, DG and EM conducted the data analysis. RB, ECochran, and FC provided critical feedback on the study design and findings. KC, KA and DG developed the manuscript with input from all authors. All authors reviewed and approved the final manuscript.
Supplemental Material
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Download MS Word (19.3 KB)Acknowledgements
The authors acknowledge research support from Harrison Sattley, an employee of Analysis Group.
Related Research Data
References
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