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ORIGINAL RESEARCH |
From the Department of Obstetrics, Gynecology and Reproductive Sciences, School of Medicine, the Medical Effectiveness Research Center for Diverse Populations, and the Department of Epidemiology and Biostatistics, School of Medicine, University of California, San Francisco, San Francisco, California; the Department of Internal Medicine, Washington University School of Medicine, St. Louis, Missouri; and Kaiser Permanente Medical Group, San Francisco, California.
Address reprint requests to: Miriam Kuppermann, PhD, MPH University of California, San Francisco Department of Obstetrics, Gynecology, and Reproductive Sciences 3333 California Street, Suite 335 San Francisco, CA 94143-0856 E-mail: kuppermannm{at}obgyn.ucsf.edu
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Abstract |
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Methods: We studied cross-sectionally 534 sociodemographically diverse pregnant women who sought care at obstetric clinics and practices throughout the San Francisco Bay area. Preferences for procedure-related miscarriage and the birth of an infant affected by Down syndrome were assessed using the time trade-off and standard gamble metrics. Because current guidelines assume that procedure-related miscarriage and Down syndrome–affected birth are valued equally, we calculated the difference in preference scores for those two outcomes. We also collected detailed information on demographics, attitudes, and beliefs.
Results: On average, procedure-related miscarriage was preferable to Down syndrome–affected birth, as evidenced by positive differences in preference scores for them (time trade-off difference: mean = 0.09, median = 0.06; standard gamble difference: mean = 0.11, median = 0.02; P < .001 for both, one-sample sign test). There was substantial subject-to-subject variation in preferences that correlated strongly with attitudes about miscarriage, Down syndrome, and diagnostic testing.
Conclusion: Pregnant women tend to find the prospect of a Down syndrome–affected birth more burdensome than a procedure-related miscarriage, calling into question the equal risk threshold for prenatal diagnosis. Individual preferences for those outcomes varied profoundly. Current guidelines do not appropriately consider individual preferences in lower-risk women, and the process for developing prenatal testing guidelines should be reconsidered to better reflect individual values.
For several decades, prenatal diagnoses of chromosomal disorders, including amniocentesis and later chorionic villus sampling (CVS), have been reserved for women aged 35 years or older at delivery.1 With the emergence of expanded maternal serum and ultrasonography screening programs, that age- and risk-based cutoff has become entrenched further. Insurance coverage for invasive testing has become more available to younger women, but only to the extent that they have been found via serum or ultrasonographic screening to be at least as high a risk as an unscreened 35 year old. Recommendations have emerged that, regardless of age, invasive prenatal diagnosis be offered only to women whose risk of giving birth to an infant with a chromosomal disorder is higher than that of an unscreened 35-year-old.2
The 35-year-old risk threshold was selected for several reasons, including resource considerations and risk-benefit concerns.3 One common rationale is that prenatal diagnosis should be limited to women whose likelihood of carrying an affected fetus is at least as high as the risk that the procedure will cause a miscarriage.4 That view assumes that women value two very different outcomes equally, ie, having a procedure-related miscarriage or a child affected by Down syndrome.5,6
Although the basis for the equal risk threshold has been questioned,3,5–8 little is known about pregnant women’s preferences. Several important questions remain unanswered, such as, is the distress of a procedure-related miscarriage really the same as that of giving birth to a child with a chromosomal abnormality? How much do preferences for those outcomes vary? What attitudes, knowledge, beliefs, and testing behaviors are associated with those preferences? We used utility assessment, a method of quantifying women’s preferences for health outcomes,9 to explore these questions in a socioeconomically, racially, ethnically, and age-diverse group of women who sought prenatal care.
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Materials and Methods |
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To ensure racial, ethnic, and socioeconomic diversity in the study population, we recruited women from several community clinics that serve women of varied races and ethnicities. We elicited preferences from pregnant women of all ages, regardless of their eligibility for invasive prenatal diagnostic testing.
Women fewer than 20 weeks’ pregnant who could read or speak English, Spanish, or Chinese were eligible. Of the 2666 women contacted, 978 were ineligible, typically because they were no longer pregnant or their gestational age was more than 20 weeks. Among the remaining 1688 women, 1084 (64.2%) participated. The most commonly cited reasons for nonparticipation were disinterest (54%) and lack of time (10%).
In the first phase of the study, 447 participants completed detailed questionnaires on attitudes, knowledge, and beliefs about prenatal testing decisions and their outcomes. From those data we developed an abbreviated questionnaire, which we administered with a series of preference elicitation exercises to the remaining 637 women. Interview materials were available in English, Spanish, and Chinese.
Interviews and Outcome Measures
Interviews began with a series of preference elicitation exercises using U-Titer, a computer-based preference elicitation tool.10 We used the time trade-off and standard gamble metrics to assess preferences.11 Both metrics generate preference values of 0 to 1, with 0 equal to death and 1 equal to an ideal outcome. They have been used widely for evaluating quality-of-life effects of clinical conditions.12–16
The time trade-off approach asks each woman to choose between living her full life expectancy with a less desirable outcome (eg, no testing followed by the birth of an infant with Down syndrome) or living a shorter time with an ideal outcome (ie, perfect knowledge of an unaffected fetus without invasive testing followed by the birth of a healthy child).17 Time spent with the ideal outcome is varied until the subject is indifferent between the two options. The time trade-off preference score is calculated by dividing the number of years with the ideal outcome by the number of years with the less desirable outcome at the indifference point.
The standard gamble metric accounts for risk preference and the value women place on a specific outcome.18 It assesses risks a subject would take to avoid an undesirable outcome that is certain. For example, a respondent might be asked to choose between a Down syndrome–affected birth for certain or an alternative with some chance of dying and a complementary chance of giving birth to a healthy child. The risks are varied until the subject is indifferent between the two options, at which point the standard gamble for Down syndrome–affected birth is equal to the chance of giving birth to a healthy child.
Interviews were conducted at locations convenient to subjects, typically their homes. At the beginning of an interview, each subject was read a description of Down syndrome–affected birth and procedure-related miscarriage. They were then asked to complete the computerized preference elicitation exercises and a paper questionnaire on demographics, reproductive history, and knowledge, attitudes, and beliefs about prenatal testing and its possible outcomes. The first 125 women were asked to complete only time trade-off preference elicitations, and the remaining 509 completed time trade-off and standard gamble exercises. After women reached 32 gestational weeks, we reviewed their medical charts to see whether they had had maternal serum screening, ultrasonographic screening, CVS, or amniocentesis.
Statistical Analyses
To investigate whether women valued equally procedure-related miscarriage and Down syndrome–affected birth, we calculated a preference difference score for each subject, defined as her preference score for procedure-related miscarriage minus her preference score for Down syndrome–affected birth. Positive difference scores indicated that they believed Down syndrome–affected birth was worse than procedure-related miscarriage, and negative difference scores indicated the opposite.
To ensure that we included data only from subjects who understood the preference measurement tasks, we applied established exclusion criteria for each metric. For time trade-off exercises, we compared each subject’s preference score for giving birth to an infant unaffected by a chromosomal abnormality to that of giving birth to a Down syndrome–affected infant. We assumed that subjects whose preference scores for giving birth to an infant with no chromosomal abnormality were lower than their preference scores for Down syndrome–affected birth (ie, had provided misordered data) did not understand the assessment task, so we did not use their time trade-off data. We also excluded data from subjects who did not provide time trade-off preference scores for both Down syndrome–affected birth and procedure-related miscarriage because both were needed to calculate the difference score.
For the standard gamble metric we compared the rank order of a subject’s standard gamble preference scores for Down syndrome–affected birth and procedure-related miscarriage to her explicitly stated preference. If her scores conflicted with her response to the question "which would be worse for you, Down syndrome–affected birth or procedure-related miscarriage, or are they both the same?" we excluded that subject’s data from the standard gamble analysis.
We began by calculating the mean, standard deviation, median, and interquartile ranges of the time tradeoff and standard gamble preference scores for procedure-related miscarriage and Down syndrome–affected birth, and for the preference difference scores. The individual preference scores and the difference scores for both metrics were not normally distributed (P < .001, Kolmogorov-Smirnov test), so we used nonparametric tests for subsequent analyses.
We used the one-sample sign-rank test to determine whether the difference scores were statistically significantly different than zero. We next explored the association between our population’s characteristics and preference difference scores. To investigate associations between preference scores and continuous variables (eg, age), we calculated the Spearman rank correlation coefficient. To determine associations between preference scores and ordered categorical variables (eg, education), we coded the categorical variable as an integer, then determined the Spearman rank correlation coefficient. We used the Kruskal-Wallis test to determine associations between preference scores and nonordered variables with more than two categories (eg, race-ethnicity), and the Wilcoxon rank-sum test for subsequent invasive prenatal testing (ie, amniocentesis or CVS). Current guidelines suggest offering tests to women who are at least 35 years old or at a similarly elevated risk, so we limited the latter analysis to subjects that met that criterion. We used 
2 and Kruskal-Wallis tests to assess differences between the misordered and ordered subgroups for categorical and ordinal data, respectively. All P values are uncorrected for multiple comparisons.
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Results |
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Table 1
summarizes the characteristics of our study population. Approximately 24% of the women were recruited at University of California, San Francisco, 7% at San Francisco General Hospital, 45% at Kaiser Permanente Medical Group, and the remaining 24% were recruited from one of several practices and clinics in the community. Although we successfully recruited a racially, ethnically, and socioeconomically diverse population, on average our respondents were older, more highly educated, and more likely to be white or black than nonrespondents (t test for age, Spearman rank correlation for education, and 2 for race-ethnicity, P < .001 for all comparisons).
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, the mean difference score (ie, preference score for procedure-related miscarriage minus preference score for Down syndrome–affected birth) was 0.09 for the time trade-off (median 0.06) and 0.11 for the standard gamble (median 0.02). Time tradeoff and standard gamble difference scores were statistically significantly different from zero (P < .001, one-sample sign-rank test), indicating that on average subjects preferred the prospect of a procedure-related miscarriage than having an infant with Down syndrome. We found also that few women equated miscarriage and Down syndrome (130 of 534, 24.3%, had time trade-off difference scores equal to zero, and 129 of 433, 29.8%, had standard gamble difference scores equal to zero). We also found substantial variation in women’s preferences.
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and 2, relationships tend to suggest a dose-response type effect, ie, the more women exhibited certain characteristics or attitudes, the more pronounced her preference was for one outcome over the other. For example, the more they answered yes to questions such as "would you have an abortion if your fetus were found to have Down syndrome?" the higher their average difference score. The more they agreed with statements such as "I would rather have a child who has Down syndrome than no child at all," the lower the difference score. Of the eight attitudinal questions, seven were statistically significantly associated with time trade-off difference scores, and all eight were statistically significantly associated with the standard gamble difference scores.
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= 0.070, P = .12; standard gamble, = 0.045, P = .35). |
Discussion |
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Second, there was substantial variation in preference scores for outcomes of prenatal testing decisions. For example, about a quarter of the women had time trade-off preference scores for procedure-related miscarriage that exceeded those for Down syndrome–affected birth by at least 0.2. Eight percent had time trade-off preference scores for Down syndrome–affected birth that exceeded those for procedure-related miscarriage by a similar amount. Such variation calls into question the notion of an average woman on whose preferences clinical guidelines should be based.
We also found that preference scores correlated as expected with eight attitudinal factors and subsequent testing behavior. We believe those associations are strong evidence of the validity of our preference assessments. They also suggest that variation in preference scores shows true differences in preference rather than measurement error. Such variation further emphasizes the need to incorporate preferences of individual women into prenatal testing decisions.
Our study had limitations. There were differences between the demographic characteristics of participants and nonparticipants. Specifically, study participants were on average older, better educated, and more likely to be white or black than nonparticipants. Consequently, preferences among nonparticipants could be different. However, we found no consistent relationship between demographic factors and the preference difference scores. We believe that the positive time trade-off and standard gamble difference scores in our study cannot be explained solely by our study population’s age, education, race, or ethnicity.
We conducted our study in the San Francisco Bay area only and we oversampled certain racial and ethnic groups, so our study group might not be representative of the United States population. However, we found that the difference scores in all four racial-ethnic groups were significantly greater than zero, suggesting that on average women in each of group found the prospect of Down syndrome–affected birth more burdensome than procedure-related miscarriage. There was substantial variation in each group, further emphasizing the need to focus on individual preferences in making testing recommendations regardless of racial or ethnic background.
Because we addressed the risk-benefit rationale for the 35-year-old guideline, the present analysis focused on only two preference scores and did not include costs. Prenatal testing is a complex decision involving risks, preferences for many additional outcomes, and issues of resource use. Future decision and cost-effectiveness analyses should address those issues. our study did not address how best to support individual decision-making concerning prenatal testing. Further research is needed to determine what information to provide pregnant women and their partners and how to assist them with choices that show those preferences.
We believe that the current guidelines of offering prenatal diagnostic testing only to women who are at least 35 years old or whose risks determined by serum or ultrasonographic screening are at least as high as unscreened 35-year-olds are not supported by preferences of women to whom these guidelines are applied. Guidelines based solely on age (or risk) do not account for substantial variation in preferences among pregnant women. We believe that development of prenatal diagnosis guidelines should account for substantial variation in preferences for Down syndrome–affected birth and procedure-related miscarriage and that clinical decision making should show the individual preferences regardless of age or risk.
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Footnotes |
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We thank Virginia Gildengorin, PhD, for statistical support. We also thank Bryna Harwood, MD, James Lewis, MD, Ruth Schaber MD, and David Walton, MD, at Kaiser Permanente, and the following physicians for their participation in this study: Albert L. Brooks, MD, Carol Eades, MD, Chris Grover, MD, Susan Sykes, MD (La Clinica de la Raza); Curtis E. Montgomery, MD, Alex Moy, MD, Lawrence Newman, MD, Laura Norell, MD, M. Ming Quan, MD, Kimberly Sorem, MD, and Jonathan Wong, MD (North East Medical Services).
Received February 10, 2000. Received in revised form May 2, 2000. Accepted May 26, 2000.
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References |
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