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					Review of Economic Evaluations on Genetic Diseases

James Jarrett and Miranda Mugford

Introduction:

       Genetic technologies often grab headlines and are commonplace in health services

across the world. This working paper is a result of a critical review of the literature [1].

While the critical review paper focuses on the economic methods used in the evaluations,

this paper will focus specifically on the disease areas in which we found full or partial

economic evaluations and give a critical summary of the results. If you are interested in

the economic methods paper, please do not hesitate to contact the authors.

Methods:

       An online search strategy was developed to find as many economic evaluations of

genetic technologies as possible between the years of 1983 and 2005. The time limit was

included as a result of a previous unpublished study by Ann Raven [2] that found no

evaluations before 1983.     The papers were then reviewed and classified by JJ, using

techniques developed by the NHSEED and the BMJ Working Party [3]. For more

specific information on the methods used, please contact the authors.

Results:

       There were 378 original articles retrieved from our search. Of which, only 37

were found to be full or partial economic evaluations. Of these, 33 focused on specific

diseases. The remaining four papers looked at multiple disease types. Breast, ovarian, and

colorectal cancer are the most commonly evaluated (accounting for 27% of papers

covering distinct disease conditions). Neonatal and prenatal screening techniques for

Cystic Fibrosis and Down Syndrome are also commonly covered (18% and 15%,

respectively). There are also substantial amounts written on various metabolic, blood, and

learning disorders.
Cancer:

          Most of the economic evaluation studies on cancer and genetics focused on cost-

effectiveness of different techniques of screening. There are five studies examining the

effectiveness of screening for familial breast and ovarian cancer (associated with

causative mutations in BRCA1 and BRCA2). In an American setting, Tengs and Berry [4]

found that screening for gene mutations was only cost-effective in populations who

already had a higher risk of having the mutation. The authors concluded that a screening

programme targeting an average risk population would not be very cost-effective due to

the low penetrance of the mutation in the average population. Eccles and colleagues [5]

found that this was also the case in the UK. Grann and colleagues [6] found that it is

likely to be cost-effective to screen the Ashkenazi Jewish population for BRCA1 and

BRCA2 mutations within the US.

          Heimdal [7] and Brain [8] and their colleagues compared different types of

screening programmes for breast cancer. Heimdal and colleagues found that, in Norway,

both the traditional cancer family clinic strategy (pedigree analysis of patients with family

history of cancer) and genetic testing for BRCA1 mutations were cost-effective (the

author‟s compared the strategies to one another, but noted that the traditional clinic has

not been evaluated sufficiently, and that possibly „no surveillance‟ may be a good

comparator to use instead). However, because the cancer family clinics were already in

place, they would be more convenient for the Norwegian health service. Brain and

colleagues looked at the problem in a slightly different way. Their study was carried out

in the UK (Wales) and analysed the health and psychological benefits associated with

multidisciplinary genetic screening techniques versus traditional screening for breast

cancer.     The authors found that the multidisciplinary approach was only marginally

beneficial.
        Reyes and colleagues [9] reported a cost-effectiveness study comparing different

methods of screening for hereditary nonpolyposis colorectal cancer (HNPCC) within the

UK. The authors found that a mixture of using the Amsterdam criteria (a family history

based approach) and microsatellite instability (MSI) method of screening was the most

cost-effective in identifying cases of predisposition to HNPCC.          This was because

although the Amsterdam Criteria is a very cheap method, it is least sensitive in detecting

carriers. The MSI method is the most expensive, but captures the proportion of carriers.

This seems supported by a study in the USA by Brown and Kessler [10] which finds that

general population screening is only cost-effective for identifying predisposition cases

when subjected to very restrictive assumptions (such as penetrance of the HNPCC

genotype being at least 80%, and a 100% accuracy of the genetic test).

       Ramsey and colleagues [11] found that, in the USA, MSI screening on patients

with newly diagnosed colon cancer, together with a personal and family cancer history, is

cost-effective for identifying cases of HNPCC versus no screening and becomes even

more cost-effective if the siblings and children of mutation carriers are identified and

screened. Vasen and colleagues [12] carried out a study in the Netherlands on the cost-

effectiveness of HNPCC surveillance using colonoscopy, and found that when compared

with no surveillance, the benefits (increased life expectancy of approx 6.9 years) are

achieved at costs of US$9,859 when discounted at 5% in 1998 dollars. However, the

authors did not perform any synthesis of costs and benefits.

       Chikhaoui and colleagues [13] compare two screening strategies (clinical

screening vs. genetic testing) for familial adenomatous polyposis (FAP) detection. The

authors find that compared to clinical screening (using family history and pedigree

analysis), predictive genetic screening is the least costly in Quebec. However, the costs to

the health system are minimised by starting the screening on the population at an earlier
Cystic Fibrosis:

       Murray and colleagues [14] carried out a HTA of screening programmes for

Cystic Fibrosis (CF), a disease that affects approximately 1 in 2000 human births in which

the mucus secreting glands become fibrous. Within the review of the health economic

literature they found that a number of researchers (15-17), have found that a combination

of prenatal and antenatal screening was the most cost-effective way to screen for CF.

Effectiveness of antenatal programmes in these evaluations was usually measured as

number of affected pregnancies avoided (aborted), or number of carriers detected. The

cost-effectiveness of screening programmes seems to be very sensitive to changes in

assumptions on the birth of „replacement‟ children, costs of the DNA test, and whether the

study takes into account screening past the initial foetus (for subsequent pregnancies).

However, in Denmark, Nielsen and Gyrd-Hansen [18] carried out a cost-effectiveness

analysis which found that introducing a prenatal screening programme could lead to a net

cost saving from both a societal and health service perspective, whether or not a

replacement child is born.      In their analysis, costs per CF patient ranged from

US$266,990-$303,398 over their lifetime, whereas estimated benefits for avoiding a case

of CF ranged from US$254,854-$533,980 (using OECD PPP [19] indexed to 1999 prices,

originally reported in Danish Kroner).

Down Syndrome:

       Four out of the five studies on antenatal screening programmes for Down

Syndrome (DS), the most common human chromosomal abnormality (trisomy 21),

compares different types of antenatal screening programmes. The technologies used in

these screening programmes were chorionic villus sampling (CVS), amniocentesis,

genetic counselling with amniocentesis, and genetic ultrasound.
       DeVore and colleagues carried out two separate cost-effectiveness analyses for

genetic ultrasound (referred to as „sonography‟ in the papers) technology. One analysis

covered a population of women under 35, and the other women over 35 [20,21]. In the

study for women under 35, the authors found that genetic sonography is cost-effective for

both high- and medium- risk patients. For those over 35, genetic sonography followed by

amniocentesis was cost-effective. However, in another study, Vintzileos and colleagues

[22] found that the benefits of first trimester genetic sonography depended on diagnostic

accuracy. The authors found that, in their setting (a hospital in the USA), there were

potential savings of $22 million for the hospital if the genetic ultrasound was 100%

accurate. Evans and colleagues [23] also found that specificity of the test was a key factor

in cost-effectiveness when comparing multiples of median and discriminant aneuploidy

detection methods.

       Only one evaluation compared the cost-effectiveness of screening programmes

across international lines [24]. That evaluation compared the costs and benefits of DS

screening strategies using nuchal translucenscy thickness (British approach) or maternal

age and maternal serum screening (American approach). The authors concluded that

financial costs of the two systems were only comparable if the first trimester ultrasound

had a sensitivity of 80% and a false-positive rate of 5% in detecting DS and that the

British strategy does not look to be beneficial in the US under any circumstances.

Hemochromatosis:

       The literature on hemochromatosis (a hereditary disorder characterised by

abnormal deposits of iron in the liver, heart, pancreas, and other organs) in this review is

limited, but Adams and Valberg [25] conclude that when compared to no screening,

genotypic screening of voluntary blood donors generates a cost-utility of US$20,042 per

QALY gained, and that the optimal strategy for the population in their study was that of
phenotyping with confirmatory genetic testing. The authors found that the model is very

sensitive to the price of the genetic test. If the test costs more than US$28, using

genotyping alone is not cost-effective. El-Serag and colleagues [26], find that genetic

testing for the hemochromatosis mutation in siblings and children of affected patients is

cost-effective   versus    no      screening   regardless   of   the   cost   of   the     test.

Hypercholesterolaemia:

       In a HTA on Familial Hypercholesterolaemia (a disease caused by mutation in the

low density lipoprotein receptor gene resulting in high levels of plasma cholesterol which

can cause coronary heart disease) Marks and colleagues [27], set out to “assess the cost-

effectiveness of strategies to screen for and treat familial hypercholesterolaemia.” The

authors identified several screening strategies including universal population screening,

opportunistic screening of patients consulted for unrelated reasons, opportunistic

screening of patients admitted for heart attack, and systematic screening of first degree

relatives of diagnosed patients.

       The authors used a simulated population of those aged 15-64 in England and

Wales taking effectiveness data from a systematic literature review and authors‟

assumptions. They found that the tracing of family members would be the most cost-

effective strategy and universal population screening the least cost-effective. The authors

also found that the earlier in a lifetime the diagnosis is made, the more cost-effective the

screening strategy becomes in identifying cases. Also, as the cost of drugs (statins) falls,

all the strategies will become more cost-effective.

Pharmacogenetics/genomics:

       None of the studies reviewed were of pharmacogenomic technologies, such as

combinations of genetic test plus targeted medication. Within this subject area, there are

more clinical and theoretical articles available than cost-effectiveness or cost-benefit
studies of particular drugs or vaccines. Danzon and Towse [28] and Veenstra and

colleagues [29] produce interesting frameworks for the analysis of pharmacogenetic

interventions, but the methods they describe are not necessarily unique to the field of

genetics.

Conclusions

       From this literature search and review, it is evident that there is little work yet

available for health policy makers on which to base decisions. The bibliography we have

collected is available via the Cambridge Genetics Knowledge Park website

(http://www.cmgp.org.uk/jjdb/index.html). It shows that several hundred papers have

been published in the last 20 years. However, the quality and robustness of much of the

work is weak.

       This review used very specific search terms and limits that could have missed data

that is available on the databases searched. This could be why some diseases commonly

tested for (such as Phenylketonuria (PKU)) did not appear in the final 37 studies. No

hand searching was done of journals and therefore selection bias (of those journals

available online) could have affected the study. Limiting the language could also have an

effect on the number of studies found. Further analysis of non-english publications

should be carried out.
References:

   1.Jarrett J., Mugford M. Genetic Health Technology and Economic Evaluation.
       Journal of Applied Health Economics and Policy. IN PRESS. 2006.

   2.Raven, Ann. Health Economics and Genetics Literature. Public Health Genetics
      Unit. Cambridge, UK. April 2001.

   3.Drummond MF, Jefferson TO. Guidelines for authors and peer reviewers of
      economic submissions to the BMJ. The BMJ Economic Evaluation Working
      Party. BMJ. 1996;313:275-83.

   4.Tengs T O and Berry D A. The cost-effectiveness of testing for the BRCA1 and
      BRCA2 breast-ovarian cancer susceptibility genes. Disease Management and
      Clinical Outcomes. 1, 15-24. 2000.

   5.Eccles DM, Englefield P, Soulby MA, Campbell IG. BRCA1 mutations in Southern
      England. British Journal of Cancer. 1998;77(12):2199-203.

   6.Grann VR, Whang W, Jacobson JS, Heitjan DF, Antman KH, Neugut AI. Benefits
      and costs of screening Ashkenazi Jewish women for BRCA1 and BRCA2. J Clin
      Oncol. 1999;17:494-500.

   7.Heimdal K, Maehle L, Moller P. Costs and benefits of diagnosing familial breast
      cancer. Dis Markers. 1999;15:167-73.

   8.Brain K, Gray J, Norman P, France E, Anglim C, Barton G and colleagues.
      Randomized trial of a specialist genetic assessment service for familial breast
      cancer. J Natl Cancer Inst. 2000;92:1345-51.

   9.Brown ML, Kessler LG. The use of gene tests to detect hereditary predisposition to
      cancer: economic considerations. J Natl Cancer Inst. 1995;87:1131-36.

   10. Reyes CM, Allen BA, Terdiman JP, Wilson LS. Comparison of selection
       strategies for genetic testing of patients with hereditary nonpolyposis colorectal
       carcinoma: effectiveness and cost-effectiveness. Cancer. 2002;95:1848-56.

   11. Ramsey SD, Burke W, Clarke L. An economic viewpoint on alternative strategies
       for identifying persons with hereditary nonpolyposis colorectal cancer. Genet
       Med. 2003;5:353-63.

   12. Vasen HF, van BM, Buskens E, Kleibeuker JK, Taal BG, Griffioen G and
       colleagues. A cost-effectiveness analysis of colorectal screening of hereditary
       nonpolyposis colorectal carcinoma gene carriers. Cancer. 1998;82:1632-37.

   13. Chikhaoui Y, Gelinas H, Joseph L, Lance JM. Cost-minimization analysis of
       genetic testing versus clinical screening of at-risk relatives for familial
       adenomatous polyposis. Int J Technol Assess Health Care. 2002;18:67-80.

   14. Murray J, Cuckle H, Taylor G, Littlewood J, Hewison J. Screening for cystic
       fibrosis. Health Technol Assess. 1999;3:i-104.
15. Cuckle HS, Richardson GA, Sheldon TA, Quirke P. Cost-effectiveness of
    antenatal screening for cystic fibrosis. BMJ. 1995;311:1460-1463.

16. Rowley PT, Loader S, Kaplan RM. Prenatal screening for cystic fibrosis carriers:
    an economic evaluation. Am J Hum Genet. 1998;63:1160-1174.

17. Wildhagen MF, ten Kate LP, Habbema JD. Screening for cystic fibrosis and its
    evaluation. Br Med Bull. 1998;54:857-75.

18. Nielsen R, Gyrd-Hansen D. Prenatal screening for cystic fibrosis: an economic
    analysis. Health Econ. 2002;11:285-99.

19. OECD. PPPs for GDP. Historical Series. http:/www.oecd.org/std/ppp/.

20. DeVore GR, Romero R. Combined use of genetic sonography and maternal serum
    triple-marker screening: an effective method for increasing the detection of
    trisomy 21 in women younger than 35 years. J Ultrasound Med. 2001;20:645-54.

21. DeVore GR, Romero R. Genetic sonography: a cost-effective method for
    evaluating women 35 years and older who decline genetic amniocentesis. J
    Ultrasound Med. 2002;21:5-13.

22. Vintzileos AM, Ananth CV, Fisher AJ, Smulian JC, Day-Salvatore D, Beazoglou
    T and colleagues. An economic evaluation of second-trimester genetic
    ultrasonography for prenatal detection of down syndrome. Am J Obstet Gynecol.
    1998;179:1214-19.

23. Evans MI, Chik L, O'Brien JE, Chin B, Dvorin E, Ayoub M and colleagues.
    MOMs (multiples of the median) and DADs (discriminant aneuploidy detection):
    improved specificity and cost-effectiveness of biochemical screening for
    aneuploidy with DADs. Am J Obstet Gynecol. 1995;172:1138-47.

24. Vintzileos AM, Ananth CV, Smulian JC, Day-Salvatore DL, Beazoglou T,
    Knuppel RA. Cost-benefit analysis of prenatal diagnosis for Down syndrome
    using the British or the American approach. Obstet Gynecol. 2000;95:577-83.

25. Adams PC, Valberg LS. Screening blood donors for hereditary hemochromatosis:
    decision analysis model comparing genotyping to phenotyping. Am J
    Gastroenterol. 1999;94:1593-600.

26. El-Serag HB, Inadomi JM, Kowdley KV. Screening for hereditary
    hemochromatosis in siblings and children of affected patients. A cost-effectiveness
    analysis. Ann Intern Med. 2000;132:261-69.

27. Marks D, Wonderling D, Thorogood M, Lambert H, Humphries SE, Neil HA.
    Screening for hypercholesterolaemia versus case finding for familial
    hypercholesterolaemia: a systematic review and cost-effectiveness analysis. Health
    Technol Assess. 2000;4:1-123.

28. Danzon P, Towse A. The economics of gene therapy and of pharmacogenetics.
    Value Health. 2002;5:5-13.
29. Veenstra DL, Higashi MK, Phillips KA. Assessing the cost-effectiveness of
    pharmacogenomics. AAPS PharmSci. 2000;2:E29.