If you don't remember your password, you can reset it by entering your email address and clicking the Reset Password button. You will then receive an email that contains a secure link for resetting your password
If the address matches a valid account an email will be sent to __email__ with instructions for resetting your password
Decision and Economic Analyses in Reproduction and Women's Health Group and the Center for Clinical and Policy Perinatal Research, University of California, San Francisco, School of Medicine, San Francisco, CA
We sought to investigate the cost-effectiveness of prenatal screening for spinal muscular atrophy (SMA).
Study Design
A decision analytic model was created to compare a policy of universal SMA screening to that of no screening. The primary outcome was incremental cost per maternal quality-adjusted life year. Probabilities, costs, and outcomes were estimated through literature review. Univariate and multivariate sensitivity analyses were performed to test the robustness of our model to changes in baseline assumptions.
Results
Universal screening for SMA is not cost-effective at $4.9 million per quality-adjusted life year. In all, 12,500 women need to be screened to prevent 1 case of SMA, at a cost of $5.0 million per case averted. Our results were most sensitive to the baseline prevalence of disease.
Conclusion
Universal prenatal screening for SMA is not cost-effective. For populations at high risk, such as those with a family history, SMA testing may be a cost-effective strategy.
Spinal muscular atrophy (SMA) is a neurodegenerative disorder characterized by death of the alpha motor neurons in the spinal cord leading to progressive proximal muscular weakness.
SMA affects approximately 1 in 10,000 live births and is the leading genetic cause of infant mortality and the second most common autosomal-recessive disorder, after cystic fibrosis.
SMA is subdivided into 4 groups. Type I, Werdnig-Hoffmann disease, is the most common and the most severe form with onset <6 months of age and death usually within the first 2 years of life, mainly secondary to respiratory failure. Type II is slightly less severe, with onset usually between 6 and 18 months of age. These children are usually able to sit but unable to walk or stand. Type III, Wohlfart-Kugelberg-Welander disease, typically has an onset during the first few years of life, but may be delayed until adolescence, and while these children are usually able to walk they may still have difficulty rising from a seated position. Type IV, or adult-onset SMA, is a mild form of disease that may not be noticed until adulthood, if at all.
SMA is caused by the homozygous deletion of the survival motor neuron (SMN1) gene in 95% of cases. The remaining cases are caused by a heterozygous deletion on one allele and a point mutation on the other.
Genetic testing is available to both identify carriers (through polymerase chain reaction identification of a single abnormally deleted SMN1 gene) and to diagnose affected individuals (2 abnormal copies). Although similar to other testing for other genetic conditions with identified mutations, there are several limitations to carrier screening. In all, 5% of the population has 2 normal copies of the SMN1 gene on one chromosome and a deletion mutation on the other.
These individuals would not be identified as carriers even though they do possess 1 abnormal SMN1 allele. Additionally, screening cannot determine which of the 4 types an affected individual will manifest.
Current controversy exists as to whether prenatal carrier screening for SMA should be offered to women or couples who are pregnant or planning pregnancy. The American College of Medical Genetics issued a statement saying that “carrier testing should be offered to all couples.”
However, the American College of Obstetricians and Gynecologists (ACOG) issued a contradictory statement that “preconception and prenatal screening for SMA is not recommended in the general population at this time.”
Moreover, ACOG stated that prior to recommending universal prenatal screening, several issues must be addressed, including cost-effectiveness analysis. As such, our study seeks to further informed debate with regard to carrier screening by investigating whether a policy of universal prenatal carrier screening would be a cost-effective strategy.
Materials and Methods
A decision analytic model (Figure 1) was created with software (TreeAgePro 2008; TreeAge Software Inc, Williamstown, MA). The study is a theoretic decision analytic model, and thus exempt from institutional review board approval as no human subjects were involved. Our theoretic cohort consisted of all women presenting for prenatal care at an early enough gestational age to allow for prenatal carrier screening. We compared a policy of universal carrier screening to that of no screening.
We divided children with SMA into 2 categories: severe disease (type I and some with type II) and milder disease (some type II, and all types III and IV). In the screening arm, women underwent serum carrier screening; if the screen was positive, their partners were also screened. If both partners were identified as carriers, an amniocentesis for fetal diagnosis was performed. We accounted for miscarriages as a result of these procedures. The model assumed that pregnancies were terminated if a fetal diagnosis of SMA was made.
As a baseline, we assumed a 100% uptake rate for each subsequent diagnostic test and that all pregnancies with a fetal SMA diagnosis were terminated. Variation in the choice of pregnancy termination was subject to sensitivity analysis.
Probabilities
Table 1 displays our baseline model inputs. The carrier screening regimen in our model is a serum probe amplification of all exons in the SMN1 gene. Carrier screening is a dosage analysis test; individuals with 50% of normal SMN1 allele levels are identified as carriers. We assumed that there would be no false-positive screens. However, for the 5% of individuals with 2 copies of the SMN1 gene on 1 chromosome, we did allow for false-negative screening. Carrier screening also does not test for more subtle point mutations. Given these limitations, we assumed an overall 90% sensitivity rate for carrier detection.
In addition, we accounted for de novo mutations. A total of 98% of SMA cases arise in a traditional autosomal-recessive inheritance pattern; however, 2% of cases arise from new mutations.
We assumed that these de novo cases occur only in offspring with at least 1 carrier parent. The possibility of 2 de novo mutations producing disease should be exceedingly rare (and there would be no effect of a single de novo mutation in a child carrier). Thus, in our model, we assume that 25% of offspring with 2 carrier parents will have SMA, 0% of offspring with no carrier parents will have SMA, and 0.005% of offspring with only 1 carrier parent will have SMA (calculated assuming a 1 in 10,000 prevalence of disease).
Costs
Cost data were derived through available literature review. All costs were inflated to 2009 dollars using the general Consumer Price Index (CPI).
Of note, as cost estimates by category of care were not available (eg, pharmacy, inpatient, physician), the general CPI was chosen to avoid overinflation by using the overall medical care component. A 3% discount rate was applied and a societal perspective was assumed.
Carrier screening testing was through dosage analysis of multiple ligation-dependent probe amplification of all exons in the SMN1 gene, at a cost of $425 per test. Diagnostic fetal testing was an analysis of exons 7 and 8 of the SMN1 gene from fetal cells obtained during amniocentesis and maternal DNA was compared to fetal DNA to evaluate for maternal cell contamination at a cost of $395 per test. This was in addition to the cost of the amniocentesis procedure itself, which was estimated from the literature.
We could find no direct data from which to estimate the lifetime cost of caring for a child with either severe or mild SMA. As such, we used the best proxies currently available in the literature. For mild disease, we assumed that the lifetime cost of caring for a child would be similar to that of caring for a child with cerebral palsy and used available estimates of total direct and indirect cost of care for such children.
To estimate the cost of respiratory support, we used published data from a national cross-sectional survey of primary caregivers for ventilator-dependent individuals.
Direct costs of care included the cost of equipment, utilities, home health personnel, health services (physician, hospital and skilled nursing facility utilization), and monthly annualized costs of 1-time purchases and home remodeling. Indirect costs were also considered, including lost wages for the primary care giver. Estimates were of true cost not charge. We inflated the estimate from 1994 to 2009 dollars using the compensation index for wages and lost income and the CPI for other costs.
Quality-adjusted life years
We only considered maternal quality-adjusted life years (QALYs) in our analysis. Given our model included the possibility of pregnancy termination as a result of information obtained from prenatal screening, considering neonatal QALYs in our model would have biased against any screening regimen. We used a 3% discount rate for QALYs.
For pregnancies that ended in fetal loss (either procedure-related miscarriage or pregnancy termination of an affected fetus) we used a maternal utility of 0.92,
which is a standard gamble utility estimate, thus applied to remaining life years. For women who have an affected child with severe disease, we used an estimate of 0.78. This estimate comes from work that used a Likert scale to specifically estimate the impact of type I SMA on parental QALY.
We applied this QALY estimate for 2 years only (average life expectancy for a child with severe disease). Beyond the 2 years, we used the reduced maternal QALY of 0.92 associated with fetal loss. For mild disease, there was no available parental QALY estimate. We therefore used the standard gamble estimate for Down syndrome (0.81) as a proxy.
We calculated total costs and QALYs to determine the incremental cost-effectiveness of offering prenatal screening for SMA. In addition, we calculated clinical outcomes, including total number of cases of SMA, pregnancy terminations, and procedure-related miscarriages. We considered cost per QALY as well as cost per case of SMA averted.
We performed sensitivity analyses to evaluate the robustness of our conclusions. For univariate analysis, we used ranges available either from literature or estimated through best clinical estimate (Table 1). For those costs and probabilities that appeared to have greatest effect on model outcomes, we performed threshold analysis to determine the range over which the outcome was still cost-effective. Additionally, we conducted a Monte Carlo simulation to test the robustness of our model to simultaneous multivariable changes in probability, cost, and utility inputs. For this simulation, costs were assumed to have a gamma distribution with SD of 50%. This is similar to a normal distribution but with a left skew, which is appropriate for medical costs given that there are often outliers in the upper cost ranges. For probability estimates we used beta distributions with SD of 20%. Beta distributions are the multivariate equivalent of binomial distributions. We ran the Monte Carlo simulation with 100,000 trials.
Results
Our model found that universal prenatal screening for SMA would reduce the number of cases of SMA by 80%, from 1 in 10,000 (baseline population risk) to approximately 1 in 50,000 (Table 2). The remaining 20% of cases are accounted for by false-negative screening and de novo mutations. In all, 12,594 women would have to be screened to prevent 1 case of SMA. The overall impact of SMA screening on procedure-related miscarriages was negligible, at <1 additional procedure-related miscarriage per 100,000 women screened.
TABLE 2Results (per 100,000 women)
Variable
Prenatal SMA screening
No screening offered
Clinical outcomes
Children with SMA, n
2
10
Procedure-related miscarriages
<1
–
Pregnancy terminations for SMA
8
–
Total cost
$44,295,289
$4,714,165
Total QALYs
2,572,954
2,572,946
Cost-effectiveness ratios
Cost per QALY
$4,889,675
–
Cost per case of SMA averted
$4,985,028
QALY, quality-adjusted life year; SMA, spinal muscular atrophy.
Little. The cost-effectiveness of prenatal screening for SMA. Am J Obstet Gynecol 2010.
In our model, prenatal screening for SMA would cost, on average, an additional $40 million per 100,000 women. This additional cost came at minimal additional QALY benefit (8 additional QALYs per 100,000 women). Thus, we found prenatal screening for SMA not to be cost-effective, at an incremental $4.9 million per QALY gained. In terms of cases averted, it would cost $5.0 million to prevent 1 additional case of SMA.
Sensitivity analysis
Figure 2 displays the results of all univariate sensitivity analyses in a modified tornado diagram. Screening was cost-effective if the column crossed a willingness-to-pay threshold in the $50,000–100,000 range. As shown, the only column that does cross this threshold is the prevalence of SMA. Thus, we find that the only circumstance in which prenatal SMA testing may be cost-effective is when there is a higher baseline prevalence of disease.
Vertical axis displays incremental cost-effectiveness ratio. Columns display changes in cost-effectiveness outcomes while varying each input. Ranges over which each input is varied are displayed in Table 1. Horizontal line is drawn at $4.9 million, as this is cost-effectiveness ratio under baseline assumptions.
LE, life expectancy; QALY, quality-adjusted life year; SAB, miscarriage; SMA, spinal muscular atrophy.
Little. The cost-effectiveness of prenatal screening for SMA. Am J Obstet Gynecol 2010.
We chose to vary the prevalence of disease down to a value of 1 in 300 to model the highest risk population. As SMA is an autosomal-recessive disorder, an individual at the highest risk of being a carrier would be one with a sibling that was diagnosed with the disease. This individual would then have a 2 in 3 risk of being a carrier themselves, multiplied by the 1 in 50 risk that their partner is a carrier and if so then a 1 in 4 risk that they would then have an affected child, for an overall disease prevalence of 1 in 300. Figure 3 displays the incremental cost-effectiveness of prenatal SMA screening while varying the baseline prevalence of disease to a 1 in 300 risk. Screening becomes cost-effective at a willingness-to-pay threshold of $100,000 per QALY once the disease prevalence is at least 1 in 1000 and at a willingness-to-pay threshold of $50,000 per QALY once the disease prevalence is 1 in 900. Screening becomes the dominant strategy (more effective and less expensive) once the disease prevalence is >1 in 800.
FIGURE 3Impact of baseline prevalence of spinal muscular atrophy
Impact of varying baseline prevalence of disease on incremental cost-effectiveness ratios. Line crosses $100,000 at prevalence of 1 in 1000, $50,000 at prevalence of 1 in 900,and 0 at prevalence of 1 in 800.
SMA, spinal muscular atrophy.
Little. The cost-effectiveness of prenatal screening for SMA. Am J Obstet Gynecol 2010.
As shown in Figure 2, the model was robust to all reasonable ranges of cost and utility estimates. It was additionally robust to changes in the life expectancy for a child with severe disease. Our model was most sensitive to the cost of carrier screening; however, even at a cost of $100 per test, which is 25% of our baseline cost estimate, screening was not cost-effective at $803,000 per QALY. In order for screening to be cost-effective at a willingness-to-pay threshold of $100,000, screening would have to cost only $44 per test (approximately 10% of baseline cost estimates).
Multivariate sensitivity analysis was performed to test the robustness of the model to simultaneous changes in probabilities, costs, and utilities using a Monte Carlo simulation. Monte Carlo results are displayed in Figure 4. Carrier screening was not cost-effective in 99.7% of the 100,000 trials using a willingness-to-pay threshold of $100,000. The 95% confidence interval (where screening was not cost-effective in 95% of the trials) was at a willingness-to-pay threshold of $700,000.
Outcomes of 100,000 trials from Monte Carlo simulation. Each dot represents single trial outcome. Ellipse represents 95% confidence interval. Dashed line represents willingness-to-pay of $100,000. As shown, >99% of points lie above this line, thus are not cost-effective.
Little. The cost-effectiveness of prenatal screening for SMA. Am J Obstet Gynecol 2010.
We find that universal prenatal screening for SMA is not cost-effective with a modeled cost of >$4 million per additional QALY gained. In the United States, interventions are generally considered cost-effective if they are in the range of $50,000–100,000 per QALY.
Universal prenatal SMA screening is well beyond this range and, moreover, in both univariate and multivariate sensitivity analyses our estimates appear robust. As with any cost-effectiveness study, the reliability of model outcomes depends on the strength of the evidence supporting estimates chosen for model inputs. Available literature was unfortunately very limited, especially with regard to the costs of having a child with SMA. However, the cost estimates had little impact on the overall findings given that our estimated cost per added QALY falls far beyond what is usually considered to be cost-effective. SMA screening does not approach the cost-effective range ($50,000–100,000 per QALY
) until the cost of severe disease is >$7 million or the cost of the mild disease is >$17 million, both of which are >20 times the baseline estimates. As such, we believe there is little chance that the basic finding that universal SMA testing is not cost-effective would change appreciably with different model inputs.
While we find that universal screening is not cost-effective, it may be cost-effective to screen in specific high-risk populations. Although there is no known ethnic or racial predisposition to SMA, the baseline prevalence is higher in women with a family history of this disease. Carrier screening in this population, or cascade screening, may well be cost-effective (based on our analysis) as long at the prevalence of disease is approximately 1 in 1000 (10 times the baseline population risk). Thus, from a cost-effectiveness standpoint, our findings support the most recent published guidelines from ACOG that prenatal screening is not recommended for the general population but should rather be limited to those with a family history of disease. ACOG further states, however, that screening should be made available to any couple that requests it and has undergone appropriate genetic counseling. Our model suggests that judged in terms of cost per maternal QALY, screening for those without a family history, regardless of whether provider or patient driven, is extremely expensive and thus a cost-effectiveness perspective would argue against such testing.
Any theoretical model, including ours, is limited in its ability to capture complexities involved in actual clinical medicine. In considering SMA screening, there are several areas where real-world decisions may be more nuanced than our model. First, due to lack of available data on patient preferences and utilities specific for SMA, we had to extrapolate some of our assumptions. The pool of currently available utility estimates was especially small, as we were specifically interested in the maternal utility of having a child with SMA, rather than the patient utility of having the disease. As such, we used what we judged to be the best utility estimate available, that of having a child with Down syndrome, to approximate the maternal utility of having a child with mild SMA. We recognize, however, that these are inherently different clinical entities, especially with regard to neurologic compromise. However, on review of available literature, our point estimate (0.81) appears reasonable, resting approximately in the middle of other parental utility estimates.
In addition, this utility falls above that of severe disease and below that of fetal loss, which makes rank order sense. In univariate sensitivity analysis our model was also robust to wide variation in this assumption.
Second, not all who elect SMA screening may choose to undergo amniocentesis for fetal diagnosis or pregnancy termination if an affected pregnancy is identified. Some may be seeking screening simply to be informed about possible outcomes. To be clear, as the rate of opting for termination of pregnancy decreases among those screened, screening using our model's perspectives and assumptions becomes less cost-effective and thus would not change our overall findings. Additionally, in real-world decision making, some patients who are found to be carriers may elect to forgo partner carrier screening and go straight to amniocentesis. While this would, on average, increase the detection rate in the screening arm, such choices would also make screening even less cost-effective as the vast majority of women who screen positive would have partners who screen negative, and thus have avoided an amniocentesis, a test that is more expensive than carrier screening.
Third, some of the costs in our model may actually be less when you factor in other clinical realities. For example, if a woman was having an amniocentesis for another reason, the cost associated with this procedure for fetal SMA diagnosis alone would be less. Again, however, given the findings of our sensitivity analyses in which costs were adjusted over a wide range, it is unlikely that minor cost adjustments would have a significant impact on results. Additionally, one might argue that the cost of carrier screening is truly less from a societal perspective, as one would presumably only need to undergo screening in the first pregnancy. In this sense, cost viewed over a woman's reproductive lifetime might be the cost of 1 test divided by the number of delivered pregnancies. However, given that our findings were robust down to 10% of the baseline cost of carrier screening, this is also unlikely to have a significant impact on results. One may also argue that our model is limited by not considering potential QALY changes for a patient's partner, family, and/or associated others. Unfortunately no model will ever be able to capture the far-reaching benefits that carrier screening may have. It is unlikely, however, given how far our baseline estimate is from reaching a cost-effective level, that even if one was able to fully consider these potential effects that carrier screening would reach a cost-effective threshold.
Fourth, as scientific advances continue, treatment options for children with SMA may became available. The life expectancy of a child with SMA may increase, and there may be a clinical advantage to earlier diagnosis. Such advances would necessitate remodeling, but given that our baseline cost-effectiveness is so high, however, we estimate that only marked changes in medical management and outcome would appreciably alter our basic findings. For example, even if new medications/technologies increased the life expectancy to 5 years (250% of our baseline estimate) screening would not be cost-effective at $3.9 million per QALY.
We hope that our main finding, that universal SMA carrier screening is not cost-effective although may be cost-effective for those with a family history of disease, can help inform the current debate with regard to screening recommendations. We are cognizant, however, that policy is not, nor should it be, entirely dependent upon economic analyses. There are many complexities to the benefits of carrier screening that are not captured in our model. The ability of couples to make informed reproductive choices is a societal good that is difficult to quantify in any economic model. Rather, we offer this model as one additional piece of information for policy makers to consider. ACOG currently recommends universal cystic fibrosis screening, for example, and while the cost of cystic fibrosis screening generally falls below accepted thresholds of cost-effectiveness, analyses suggest that such screening is not cost-effective in all populations.
As our scientific knowledge regarding the genetic basis for disease continues to expand, the number of conditions that can be screened for prenatally will likely increase. Our findings suggest, however, that universal prenatal screening for rare genetic conditions using single-test assays may prove too expensive to be cost-effective from a societal perspective. The development of new high-throughput technologies that allow multiple genes to be analyzed in a single screening platform will likely lower the cost of individual screening protocols and may provide more cost-effective universal screening regimens.
References
Kostova F.V.
Williams V.C.
Keemskerk J.
et al.
Spinal muscular atrophy: classification, diagnosis, management, pathogenesis, and future research directions.
Dr Caughey is supported by the Robert Wood Johnson Foundation as Physician Faculty Scholar RWJF-61535.
Drs Ecker and Caughey served as senior authors.
Cite this article as: Little SE, Janakiraman V, Kaimal A, et al. The cost-effectiveness of prenatal screening for spinal muscular atrophy. Am J Obstet Gynecol 2010;202:253.e1-7.
Reprints not available from the authors.
The racing flag logo above indicates that this article was rushed to press for the benefit of the scientific community.
This month's issue includes 8 articles that describe research presented at the 2010 meeting of the Society for Maternal-Fetal Medicine (SMFM) in Chicago on February 4-6. From 1256 abstracts submitted, 86 were selected by the Society for oral presentation. Authors of these 86 abstracts were invited to submit their manuscripts through the “Fast-Track” process, in which AJOG reviewers provided rapid reviews in time to allow revision to meet the deadline for inclusion in this issue. These fast-track articles are easily identified by the checkered racing flags on the first page of each as well as next to their titles in the Contents section.
Little et al1 pose an important question: would the universal offer of carrier screening for spinal muscular atrophy (SMA) during prenatal care be cost-effective, ie, provide good value for money spent? The rapid expansion of the availability of molecular genetic tests for rare disorders, with approximately 1700 tests currently available,2 poses a challenge to health care providers and payers. We as a society do not have sufficient funds to pay for all possible genetic tests, and prioritization in some form must be undertaken.
00062-1&id=gr1.jpg){kind=link}
00062-1&id=gr2.jpg){kind=link}
00062-1&id=gr3.jpg){kind=link}
00062-1&id=gr4.jpg){kind=link}