Our analysis indicates that adding %CDT to questionnaire based one-time screening is cost-effective in typical primary care conditions. In 50 year olds, the Questionnaire-%CDT strategy costs $15,500 per QALY gained when compared to the Questionnaire Only strategy. Compared with the Questionnaire Only strategy, the Questionnaire-%CDT strategy was favored at a threshold of $50,000/QALY when the prevalence of unhealthy alcohol use exceeded 15% and the age at screening was <60 years. The Questionnaire Only strategy dominated the No Screening strategy in virtually all age cohorts. Screening with the %CDT test alone was not cost-effective.
We provide evidence for intensifying screening to detect unhealthy alcohol use in primary care by adding a %CDT test when questionnaire screening is negative. Our analysis differs from a cost-benefit analysis conducted by Dillie and colleagues (2005)
which suggested that adding %CDT to physician interview is cost saving, meaning that it achieved better outcome at a lower cost. We found that adding %CDT to questionnaire screening was cost-effective (achieved better outcome but at a higher, though generally acceptable, cost) but not cost-saving. Some people informally summarize such interventions as “good value.” Unlike the previous analysis, we accounted for incomplete follow-up of %CDT, potential need for a second visit to address the positive result, and poor provider performance in delivering treatment (Burman et al., 2004
; Saitz et al., 2003
). Our analysis also included the long term cost and effects of screening with %CDT and included patient time costs and out of pocket expenses (i.e., the societal perspective). The base case ICER value of $15,500/QALY compares favorably with the cost-effectiveness of other currently accepted screening programs—e.g. one-time HIV screening ($33,000/QALY) (Paltiel et al., 2006
) or colonoscopy every 10 years compared with annual fecal occult blood testing or no screening ($12,000 to 18,000/life year; Pignone et al., 2002
Our conclusion also differed from Coulton and colleagues (2006)
who found the cost per patient screened was 20-fold greater for %CDT compared with questionnaire based screening in Welsh males. This group did not, however, analyze the incremental cost-effectiveness of adding %CDT to questionnaire-based screening as in the current study and did not account for potential downstream costs saved, mortality avoided, and quality of life improved.
There are several limitations to this work. There is no single estimate for the prevalence of unhealthy alcohol use in primary care. Prevalence varies by gender, race, ethnicity, geography, and duration but has been reported in multiple studies (Manwell et al., 1998
; Taj et al., 1998
) to be more than 20% using the current NIAAA definition we adopted for our analysis. We chose prevalence estimates from a study by Manwell and colleagues (1998)
in which 21,282 patients in Wisconsin were screened for unhealthy alcohol use. That study reported a 90-day prevalence
of unhealthy alcohol use of 23%, combined for all ages and both genders. The study included one of the largest U.S. primary care samples available and it provided data about the spectrum of unhealthy alcohol use. Our sensitivity analysis suggests the Questionnaire-%CDT strategy would still be cost-effective (at the $50,000/QALY threshold) in a lower prevalence scenario when the age at screening is less than 60 years.
There is also no single way to administer brief intervention and therefore no single estimate for the transition rate from at-risk drinking to safe drinking levels. We believe our choice for the value of the transition rate (i.e., 39%) after brief intervention was conservative. Other studies such as Project Treat (Fleming et al., 1997
) using a longer initial BI and incorporating follow-up contacts have described the effect to be larger but we believe a one-time, 5 to 10 minute intervention was the one most likely to resemble how physicians actually conduct brief intervention. Comparisons with other brief intervention trials such as those included in a recent systematic review (Beich et al., 2003
) are limited by exclusion of subjects with lower levels of risky alcohol.
Another limitation of the Markov modeling technique we used is that the transition probabilities depend only on the current state and not on the history of past states. For example, individuals in the at-risk drinking state in a given 1-year cycle had the same probability of transitioning into other states regardless of their drinking state in prior cycles. We did not have information about the rate of transition from safe to at-risk drinking for an individual with a prior history of atrisk drinking compared with someone without this history. We obtained information about transitions in drinking behavior from a study by Kerr and colleagues (2002)
based on the National Health Nutrition Examination Survey. Transition rates provided by Kerr and colleagues represent the rate of transitions at the aggregate level. This includes individuals with and without a prior history of at-risk drinking. We therefore believe that the transition rates we used are an accurate representation of the transitions from safe to at-risk drinking, at the aggregate level. For individuals with a history of alcohol dependence, this “amnestic” property of Markov models was mitigated by the high rate of relapse built into the Recovery state.
Other limitations include absence of conditional diagnostic test performance data for %CDT (i.e., the sensitivity and specificity in a population already having tested negative by questionnaire). We believe biomarker screening has a diagnostic performance that is independent from questionnaire performance. Our estimate for %CDT performance to detect unhealthy alcohol use was a conservative choice from the limited trials set in general primary care. Had we chosen to use discrete diagnostic performance data for detecting very heavy drinkers, as in the previously mentioned sensitivity analysis, the economic implications would not have changed substantially.
We also did not have information about the effectiveness of brief intervention or alcohol treatment in a group testing negative by questionnaire. Brief intervention is likely to be less successful in a group testing negative by questionnaire. Such individuals may be feigning low risk use or they may be infrequent risky drinkers, and in either case less likely to change, although the exact magnitude of the differential effectiveness is not known.
We did not have information about the clinical effect of ordering a blood test in patients denying unhealthy alcohol use. Patients who take offense from being asked to confirm their reported drinking behavior with %CDT may decide not to discuss their alcohol use or other medical problems as freely with their provider. They may even decide to sever relations with this provider. We believed the frequency of these untoward consequences would be low and therefore did not model any costs for the deterioration or discontinuation in the patient-provider relationship. We feel the decision to not to model these costs, however, was still a conservative choice given that mention of objective corroboration of a person’s report with %CDT will likely prime an admission of unhealthy use for a large percentage of primary care patients, thereby obviating the need and cost for the test. In addition, at least 1 study suggests that the use of %CDT can provide motivation for some patients to reduce their alcohol use (Fleming et al., 2004
). The exact direction of the bias imposed by our balanced modeling assumptions (i.e., that all patients who screened negative by the questionnaire would undergo the blood test and that no patient would voluntarily disclose their drinking status upon broaching the issue of biomarker screening) is unknown and represents area for future inquiry.
Lastly, we did not model all possible consequences of a false-positive %CDT result. There is no consensus for the workup of elevated %CDT results and false-positive results may occur in patients underreporting alcohol use (i.e., the gold standard interviews used to assess performance are imperfect). Future research should assess %CDT performance and treatment effectiveness in a cohort testing negative by questionnaire, patient and provider acceptability of the Questionnaire-%CDT strategy, and the implications of false-positive %CDT results.
In conclusion, adding %CDT to questionnaire based one-time screening for unhealthy alcohol use was cost-effective in typical primary care conditions and, at minimum, clinicians should screen all patients with a questionnaire. Some clinicians may consider ordering %CDT after a negative screening questionnaire for adults up to age 60 when the prevalence of unhealthy alcohol use is 15% or more. However, despite its cost-effectiveness, issues around effectiveness of brief intervention in a questionnaire negative group, patient acceptability of blood testing in this same group, and management of false-positive results should be better studied before we can recommend widespread use of %CDT.