Cost-Effectiveness of Newborn Screening for Spinal Muscular Atrophy in The Netherlands

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Abstract

Spinal muscular atrophy (SMA) is a rare genetic disorder that causes progressive muscle weakness and paralysis. In its most common and severe form, the majority of untreated infants die before 2 years of age. Early detection and treatment, ideally before symptom onset, maximize survival and achievement of age-appropriate motor milestones, with potentially substantial impact on health-related quality of life. Therefore, SMA is an ideal candidate for inclusion in newborn screening (NBS) programs. We evaluated the cost-effectiveness of including SMA in the NBS program in The Netherlands.

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Single-Dose Gene-Replacement Therapy for Spinal Muscular Atrophy

W. Arnold, Louise Rodino‐Klapac, Thomas Prior … (2017)

Spinal muscular atrophy type 1 (SMA1) is a progressive, monogenic motor neuron disease with an onset during infancy that results in failure to achieve motor milestones and in death or the need for mechanical ventilation by 2 years of age. We studied functional replacement of the mutated gene encoding survival motor neuron 1 (SMN1) in this disease.

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Enhanced secondary analysis of survival data: reconstructing the data from published Kaplan-Meier survival curves

Patricia Guyot, AE Ades, Mario JNM Ouwens … (2012)

Background The results of Randomized Controlled Trials (RCTs) on time-to-event outcomes that are usually reported are median time to events and Cox Hazard Ratio. These do not constitute the sufficient statistics required for meta-analysis or cost-effectiveness analysis, and their use in secondary analyses requires strong assumptions that may not have been adequately tested. In order to enhance the quality of secondary data analyses, we propose a method which derives from the published Kaplan Meier survival curves a close approximation to the original individual patient time-to-event data from which they were generated. Methods We develop an algorithm that maps from digitised curves back to KM data by finding numerical solutions to the inverted KM equations, using where available information on number of events and numbers at risk. The reproducibility and accuracy of survival probabilities, median survival times and hazard ratios based on reconstructed KM data was assessed by comparing published statistics (survival probabilities, medians and hazard ratios) with statistics based on repeated reconstructions by multiple observers. Results The validation exercise established there was no material systematic error and that there was a high degree of reproducibility for all statistics. Accuracy was excellent for survival probabilities and medians, for hazard ratios reasonable accuracy can only be obtained if at least numbers at risk or total number of events are reported. Conclusion The algorithm is a reliable tool for meta-analysis and cost-effectiveness analyses of RCTs reporting time-to-event data. It is recommended that all RCTs should report information on numbers at risk and total number of events alongside KM curves.