مقرون به صرفه بودن غربالگری نوزادان گسترده در تگزاس

Objective Texas House Bill 790 resulted in the expansion of the newborn screening panel from 7 disorders to 27 disorders. Implementation of this change began in 2007. The objective of this study was to estimate the incremental cost-effectiveness of the expanded newborn screening program compared with the previous standard screening in Texas. Methods A Markov model (for a hypothetical cohort of Texas births in 2007) was constructed to compare lifetime costs and quality-adjusted life-years (QALYs) between the expanded newborn screening and preexpansion newborn screening. Estimates of costs, probabilities of sequelae, and utilities for disorder categories were obtained from a combination of Texas statistics, the literature, and expert opinion. A baseline discount rate of 3% was used for both costs and QALYs, with a range of 0% to 5%. Analyses were conducted from a payer's perspective, and so only direct medical cost estimates were included. Results The lifetime incremental cost-effectiveness ratio for expanded versus preexpansion screening was about $11,560 per QALY. The results remained robust to both deterministic and probabilistic sensitivity analyses. Conclusions Expanded newborn screening does result in additional expenses to the payer, but it also improves patient outcomes by preventing avoidable morbidity and mortality. The screened population benefits from greater QALYs as compared with the unscreened population. Overall, expanded newborn screening in Texas was estimated to be a cost-effective option as compared with unexpanded newborn screening.

Newborn screening involves laboratory analysis of blood samples from newborns to detect inborn errors of metabolism and allows timely diagnosis of serious and life-threatening conditions. Screening should be conducted in the first week of a baby's life to ensure treatment initiation before the age of 4 weeks. Timely treatment helps prevent irreversible mental retardation, physical disability, and death in most cases [1]. Newborn screening started in the United States in early 1960s when Dr. Robert Guthrie developed a bacterial inhibition assay for identifying infants with phenylketonuria (PKU). His technique of collecting blood samples on filter paper made it possible to implement PKU screening at the population level [2]. Gradually, more disorders were added to the newborn screening panel. The use of tandem mass spectrometry (MS/MS) has made it possible to screen for as many as 50 disorders by using the same blood specimen. With the ability to screen for more disorders, most US states expanded their newborn screening panel although the expansion process varied greatly across states. The economic viability of these expansions has been studied by many researchers. In 2002, Schoen and Baker [3] reported that screening for multiple disorders with MS/MS yields an incremental cost-effectiveness ratio (ICER) of $5827 per quality-adjusted life-year (QALY). Of the newly added conditions, medium-chain acyl-CoA dehydrogenase deficiency (MCADD) is the most common, affecting about 1 in 20,000 of all newborns in the country. A few studies have been based on the cost-effectiveness of this condition alone. Insinga et al. [4], Venditti et al. [5], and Tran et al. [6] reported that universal screening for MCADD by using MS/MS is a cost-effective option. Two studies based in California focused on MCADD and several other conditions and reported that MS/MS screening is a cost-effective strategy for most conditions, except congenital adrenal hyperplasia or galactosemia [7] and [8]. A Canadian study assessed the expansion of the existing screening system in Ontario and concluded that the average cost of screening for PKU plus 14 other disorders is Can $95,000 per life-year gained [9]. It is important to note that in each of the studies, comparisons may differ. Reasons for this include differences in the base case, patient population, and number of disorders already being screened, and measures of cost-effectiveness used. Such differences will automatically impact the results of an economic analysis that is always relative to the baseline comparator. The newborn screening panel in Texas was expanded when House Bill 790 mandated that the state should offer screening for at least 28 conditions recommended by the American College of Medical Genetics [10]. In 2007, Texas began to screen for 27 of the 29 recommended conditions. This was a large increase from the 7 disorders that were included in the panel prior to this expansion. Texas performs two screens on newborns by using separate blood samples obtained at the ages of 24 to 48 hours and 7 to 14 days, respectively. Blood samples from infants who test positive after the second screen need to be sent for confirmatory testing.

As shown by the results of this analysis, expanded screening may cost an additional $11,560 per QALY at the base discount rate of 3%. Although the absolute difference in the effectiveness of the two strategies at a population level is relatively small, at 0.002829 QALYs, it can potentially make a significant difference for the infants detected with one of the disorders. For most of the disorders, expanded screening is associated with more costs coupled with greater quality of life. For ASA and CIT, screening costs an estimated additional $10,000 per QALY at the base rate of 3%, which is likely due to the higher cost of treatment for these disorders. Although screening results in higher survival among patients with ASA and CIT, rates of mental retardation tend to remain high among the survivors, resulting in poor quality of life for survivors. For HCY, screening not only costs less due to lower treatment costs but also results in greater quality of life due to the reduced likelihood of adverse outcomes in the screened group. A vast majority of the unscreened patients are at the risk of lens dislocation and chronic skeletal abnormalities as they grow older, leading to significant direct medical costs and reduced quality of life. In contrast, only a few of the screened patients run the risk of lens dislocation or spinal osteoporosis. Therefore, screening is the dominant strategy for HCY. For maple syrup urine disease, there is a stark contrast in the QALYs for screened versus unscreened patients. This can be explained by the extremely high mortality (which translates to zero QALYs) in the first two years of life for children who may be diagnosed late. Screening for GA-I also results in a substantial increase in QALYs, while still remaining cost-effective. The ICER of screening and treatment for MCADD is about $633 per QALY, which is lower than some of the published estimates [4]. Possible reasons for this difference could be the use of different model inputs. Furthermore, the treatment plan for cases of MCADD diagnosed via screening or clinical symptoms would be very similar, yet QALY improvement in screened cases is significant due to the reduced risk of mortality. Screening for COAD is also cost-effective, with the ICER for screened group at about $1800 per QALY. Timely intervention is crucial in this group of disorders, and patients can potentially have a better quality of life without incurring extremely high treatment costs. Results of the one-way sensitivity analyses point to several variables that may impact the results of the cost-effectiveness analysis. Study results were sensitive to variations in discount rate because it impacts all the costs and utilities after the first year of life. Within the cost category, cost of false positives and cost associated with special diet were the most influential variables. If the cost of ruling out false-positive screens is very high, it can potentially impact the cost-effectiveness of the program. The cost of special diet impacts every child who tests positive for any of the disorders and is placed on a special diet. The cost of carnitine supplementation is also an important variable in the cost category. Although there is no evidence-based recommendation for carnitine supplementation in patients with MCADD, according to expert opinion, carnitine supplementation is frequently recommended, especially in the United States (this practice may not be followed in European countries) [30] and [31]. In our model, we included the cost of carnitine supplementation for patients with complications related to MCADD [30] and [31]. Because MCADD is the most prevalent condition included here, cost of carnitine can affect a significant number of patients each year. Within the probability category, a significant decline in the probability of death due to some disorders is seen for the screened versus unscreened populations. A decline in mortality is the only major difference between the screened and unscreened patients when other sequelae do not differ much despite screening. This may explain the influence of probability of death for ASA and CIT as an influential variable in this category. The probability of neurological damage also differs significantly for the screened versus unscreened populations of patients with GA-I and patients with COAD. So, these variables also impact the overall study results. For the categories of utility values used in the Markov model, the utility of being on treatment (with special diet) without any additional complications impacts most of the members of the cohort. Consequently, this variable is influential as shown by the tornado diagram. Results of the overall cost-effectiveness analysis are somewhat comparable with the results of other studies done in the past. Other studies may differ in terms of the comparators included, perspective of analysis, costing year, and country. For example, the base-case results of the current study show that the ICER for expanded screening was approximately $11,560 per QALY at a discount rate of 3%. In their 2002 study, Schoen and Baker [3] reported their base-case estimate as $5827 per QALY. Their results were based on estimates of a number of disease states, including PKU. While the current study includes cost-effectiveness estimates of screening for most of the disorder categories used by Schoen and Baker, it does not include cost and effectiveness analyses for PKU. Inclusion of PKU may have changed the results of the study because it is a much more prevalent condition as compared with many other disorders. Similarly, the current study differs from the analysis by Carroll and Downs [7] in terms of the disorders included and the utility estimates for sequelae. The current study results of $11,560 per QALY are also higher than the cost-effectiveness estimate provided by Feuchtbaum and Cunningham [8]. According to their estimates, screening cost $1628 per QALY in the base-case estimate. Instead of allocating separate costs to each of the disease sequelae, they had used an average estimate of $1 million for the cost of lifetime treatment and follow-up. Their estimate was derived from a research article based on a Centers for Disease Control and Prevention report published in 2003 [25]. The source article, however, elaborates that most of the costs in this $1-million estimate are based on the productivity loss due to lost wages and early mortality. The current study does not include productivity losses incurred either by the parents or by the patients (after they reach adulthood), which may be different than some other studies conducted in the United States. If indirect costs were included in the present study, the results may be more comparable to the conclusions of Feuchtbaum and Cunningham. Study results also share some similarities with those of a more recent study based on the cost-effectiveness of expanding newborn screening in Ontario, Canada [9] In their study, Cipriano et al. [9] reported that if MS/MS is used for screening newborns for PKU along with other metabolic disorders, it would only be cost-effective to include PKU and 14 other conditions on a combined newborn screening panel. The inclusion of maple syrup urine disease, GA-I, COAD, and MCADD and other fatty acid disorders along with PKU would be cost-effective at less than C$70,000 per life-year gained. Results of the current study also suggest that screening for these conditions is cost-effective. There are some key differences, however, between the current study and the Cipriano study, such as the use of life-years versus quality-adjusted life-years. Furthermore, the Cipriano study was proposing the expansion of newborn screening in Ontario. Therefore, they included the disorders in a stepwise manner where the decision to include each successive disorder in the panel could be based on incidence, prevalence, and the availability of effective treatment. While these are valid points to consider before any expansion of an existing program, they may not be useful for estimating the cost-effectiveness of an expansion that has already taken place (such as in the case of Texas), where it may be more relevant to consider simultaneous inclusion of a number of disorders.