GIFT, THOMAS L. PhD*; WALSH, CATHLEEN DrPH*; HADDIX, ANNE PhD†; IRWIN, KATHLEEN L. MD, MPH*
IN 1999 APPROXIMATELY 660,000 CASES of chlamydial infection were reported to the Centers for Disease Control and Prevention (CDC; Atlanta), making it the most commonly reported sexually transmitted disease (STD)in the United States. 1 For the same year, approximately 360,000 cases of gonorrhea were reported. Since the populations infected with one or the other infection often overlap, there may be value in presumptively treating individuals infected with chlamydial infection for gonococcal infection or vice versa. Depending on the rate of coinfection and the cost of sequelae, such treatment approaches may be cost-effective in some clinical settings.
Because many Neisseria gonorrhoeae and Chlamydia trachomatis infections are asymptomatic, case detection depends on screening. The CDC has recommended gonorrhea screening for pregnant women, sexually active adolescents, and women with multiple sex partners 2–4 and chlamydia screening for pregnant women, sexually active adolescents, and women >20 years of age who report inconsistent use of condoms or who have new or multiple sex partners. 5 The United States Preventive Services Task Force recommends routinely screening all sexually active women aged 25 years and younger for chlamydial infection 6 and for gonorrhea if they have had two or more sex partners in the past year or have a history of repeated episodes of gonorrhea. 7 The American Medical Association recommends screening sexually active adolescents for both chlamydial infection and gonorrhea. 8
Since 1985, the CDC has recommended that patients treated for N gonorrhoeae infection also be treated for C trachomatis infection. 2,9,10 The 1998 recommendation states: “Patients infected with N gonorrhoeae often are coinfected with C trachomatis; this finding led to the recommendation that patients treated for gonococcal infection also be treated routinely with a regimen effective against uncomplicated genital C trachomatis infection. Routine dual therapy without testing for chlamydial infection can be cost-effective for populations in which chlamydial infection accompanies 20%–40% of gonococcal infections, because the cost of therapy for chlamydial infection (e.g., $0.50–$1.50 for doxycycline) is less than the cost of testing.”2 The CDC's dual therapy recommendation could be interpreted to discourage testing for C trachomatis. However, the CDC's 1993 chlamydial infection prevention and management recommendations encourage screening of all women at risk, which would include women with gonorrhea. 5 In settings where universal screening is not implemented, the dual therapy guideline offers an alternative control strategy for concurrent chlamydial infection.
A disadvantage of presumptive treatment for C trachomatis infection without testing is that sex partners of the index patient may be less likely to be tested or treated; treatment without testing precludes the laboratory's reporting of a positive C trachomatis test to local health authorities, which would have triggered notification of sex partners. If infected sex partners are not treated, chlamydial infection may reoccur in the index patient. This is of particular concern to women, because chlamydial reinfections substantially increase the risk of upper-tract infection and pelvic inflammatory disease (PID). 11 Another disadvantage of dual therapy without testing is the potential to increase the prevalence of antimicrobial-resistant strains of both C trachomatis and N gonorrhoeae. Clinically significant resistance of C trachomatis to commonly used antibiotics has been reported but is believed to occur rarely. 12,13 Resistance of N gonorrhoeae to several antibiotics, including tetracyclines, penicillins, and fluoroquinolones, has been established, and recently its decreased susceptibility to azithromycin was recognized. 14,15
The purpose of the current analysis was to examine the effectiveness and cost-effectiveness of routine dual therapy for C trachomatis infection without testing for C trachomatis in women infected with N gonorrhoeae who lack symptoms or signs. This study updates an earlier cost-effectiveness analysis 16 of dual therapy by incorporating the effects of (1) using ceftriaxone and cefixime, which are the currently recommended primary treatments for N gonorrhoeae infection but not effective against C trachomatis2,17 and (2) using new nonculture tests for C trachomatis that increase the accuracy and feasibility of testing for C trachomatis. 18 Some available nonculture tests make it possible to test for both C trachomatis and N gonorrhoeae with the same specimen.
We conducted a decision analysis using DATA 3.5.7 software (TreeAge Software, Williamstown, MA) to model several strategies for testing and treatment of chlamydial infection and gonorrhea in a hypothetical cohort of asymptomatic women (Figure 1). We focused on asymptomatic women who had no indication (signs or partners with symptoms) for presumptive treatment because up to 70% of chlamydial infections and 30% to 80% of gonococcal infections in women are asymptomatic 19 and because we assumed that women presenting to a healthcare provider with symptoms or signs would be treated for both infections regardless of testing protocols. 2 We assumed that all patients would be tested according to one of the three algorithms listed below using a nonrapid test that would require women testing positive to be recalled for treatment.
We conducted a healthcare system perspective analysis. We assessed direct medical costs, including costs for testing (including clinician time), treatment (including the cost of a return visit to the facility for treatment), and sequelae (such as PID) incurred by the initial site of care or sites that cared for sequelae of the initial infection, even if they occurred several years later. Patients’ costs, lost productivity, pain, and suffering were not included.
We modeled three testing and treatment algorithms that represent a progression toward a steadily more aggressive approach to testing and treatment for chlamydial infection.
1. Co-Treat. Test for N gonorrhoeae; do not test for C trachomatis. Presumptively treat women with a positive test for gonorrhea for chlamydial infection (baseline).
2. Test. Test for both infections; treat only patients with positive tests. Treat women who test positive for N gonorrhoeae for gonorrhea; treat women who test positive for C trachomatis for chlamydial infection.
3. Test/Co-Treat. Test for both infections. Treat women who test positive for N gonorrhoeae for gonorrhea and chlamydial infection, and treat women who test positive for C trachomatis for chlamydial infection. This algorithm was considered because available tests commonly used for C trachomatis have sensitivities as low as ≤0.70, meaning that some patients infected with C trachomatis will test falsely negative. However, some of these patients may be dually infected and test positive for N gonorrhoeae. Adding co-treatment makes it possible to increase the number of C trachomatis infections treated even when testing for C trachomatis.
Hereafter, we refer to these algorithms by the three terms used above.
Except for disease prevalence and coinfection rates, variable values used in the baseline model and ranges used in sensitivity analysis were obtained from the literature (Table 1). Disease prevalence and coinfection rates were selected to be applicable to a broad range of clinical settings and population groups. We defined the coinfection rate as the proportion of women infected with N gonorrhoeae who were also infected with C trachomatis.
Our model considered the performance on endocervical specimens of two commonly used tests for C trachomatis, a nucleic acid hybridization test (PACE 2; Gen-Probe, San Diego, CA) and a nucleic acid amplification assay (ligase chain reaction [LCR]; Abbott Laboratories, Abbott Park, IL). We also modeled three tests for N gonorrhoeae: culture, a nucleic acid amplification assay (LCR, also produced by Abbott Laboratories) and the combination nucleic acid hybridization test produced by Gen-Probe, the PACE 2C, which allows testing for both C trachomatis and N gonorrhoeae with the same sample. When the initial combination test result is positive, follow-up testing with the residual sample is required to identify whether C trachomatis or N gonorrhoeae is present when pathogen-specific identification is necessary for reporting or other purposes. 18 Thus, all tests require notifying infected patients of their test results after their initial visit and require a return visit or referral to a pharmacy for treatment (as a baseline, we assumed patients would return to their point of care for treatment). We modeled two CDC-recommended treatments for C trachomatis infection (azithromycin and doxycycline) and uncomplicated N gonorrhoeae infection (cefixime and ceftriaxone). 2
Our outcome was the number of cases of PID arising from gonorrhea and chlamydial infections in a hypothetical cohort of 1000 women. We assumed that PID would develop in 6% of successfully treated cases of gonorrhea, chlamydial infection, or coinfection and in 20% of untreated cases of infection due to one or both organisms. 5,20–24
Test costs include those for the test kits, reagents, necessary collection and processing equipment, and labor time for collection and processing. 25 Labor cost was estimated at $16.86 (U.S.) per hour ($13.49 per hour plus 25% for fringe benefits). 26 Costs for the pelvic examination were not included because we sought to analyze the cost differences when applying the algorithms in settings where a pelvic examination would be routinely conducted. Therefore, we included only the additional costs that providers would incur for each of the three testing and treatment algorithms.
For the baseline cost per case of PID, we included the cost of care for acute PID and its sequelae of infertility, chronic pelvic pain, and ectopic pregnancy over the lifetime of the patient. The costs of sequelae occurring after the acute infection were discounted at 3% per year. 27
All costs were adjusted to January 2000 dollars using the medical care component of the Consumer Price Index. 28 Because many of the variables may take different values in various settings and because there is uncertainty about several others, sensitivity analyses were performed over the ranges indicated in Table 1. 2,5,13,18,20,23,25,27,29,30,38–66 Where 95% CIs were reported in the literature or could be derived from the published data, they were used as the ranges for sensitivity analysis. Otherwise, expert opinion was used.
We calculated the program cost and net cost of the testing and treatment algorithms. We defined the program cost as the cost of testing and treatment, including the cost to notify patients of positive test results and the cost of the visit to receive treatment. We defined the net cost as the program cost minus the expected PID costs that were averted because of the testing program. Therefore, the net cost represents the cost of the program after savings from the cases of averted PID were subtracted. We defined the average cost-effectiveness as the net cost per case of PID averted for a given algorithm when compared with the baseline algorithm of Co-Treat. The incremental cost-effectiveness was defined as the net cost per case of PID averted for a given algorithm compared with the next-less-effective algorithm. The incremental cost-effectiveness thus showed the additional cost per additional case of PID averted when a testing and treatment algorithm was switched to the next-most-effective algorithm among the three that were analyzed.
As a part of the sensitivity analysis, we calculated threshold test costs with different testing combinations. The threshold test cost was defined as the test cost at which two algorithms had the same net cost. Varying the test cost from the threshold value made one algorithm less costly than the other. Threshold values were calculated to evaluate the robustness of the results achieved when the baseline values (Table 1) were used.
Regardless of the tests considered, the Test/Co-Treat algorithm averted the greatest number of cases of PID, followed by the Test algorithm (Table 2). 67 The Co-Treat algorithm averted the fewest cases of PID. In all cases, the greatest incremental reduction in cases of PID was realized when comparing the Test algorithm with the Co-Treat algorithm. The reduction varied between 18% and 35% and depended on test selection. A further reduction of 1% to 2% was realized when comparing the Test algorithm with the Test/Co-Treat algorithm.
Table 2 shows the program cost and net cost for each of the three algorithms using a variety of test combinations for C trachomatis and N gonorrhoeae. The results presented are based on treatment with azithromycin for C trachomatis infection and treatment with cefixime for N gonorrhoeae infection. The net costs calculated using these treatments were essentially equivalent to or lower than the net costs calculated for the other treatments considered (doxycycline and ceftriaxone). All costs in Table 2 were calculated with all variables set to the baseline values in Table 1.
When using the nucleic acid hybridization assay for C trachomatis, either alone or in combination with the nucleic acid hybridization assay for N gonorrhoeae, the program costs for the Test and Test/Co-Treat algorithms were higher than for the Co-Treat algorithm, but net costs were similar. When using nucleic acid amplification assay, net costs for the Test and Test/Co-Treat algorithms were higher than for the Co-Treat algorithm. The additional cost resulted in a greater number of treated infections and fewer sequelae.
Regardless of the choice of test, the Test/Co-Treat algorithm had a net cost similar to but slightly higher than that of the Test algorithm. The Test/Co-Treat algorithm averted a greater number of cases of PID than the Test algorithm but also resulted in a larger degree of overtreatment than either of the alternative algorithms. At the baseline values shown in Table 1, all three algorithms resulted in treating some women for infections they did not have. The number of women appropriately and inappropriately treated under each of the three algorithms is shown in Table 3. The inappropriate treatment was most common in the Co-Treat and Test/Co-Treat algorithms, the two algorithms in which at least some treatment for C trachomatis was initiated on the basis of test results for N gonorrhoeae. Overtreatment was minimized under the Test algorithm because only women whose tests for C trachomatis were positive received treatment for C trachomatis.
The cost results were similar if we dropped the assumption that patients would return to the provider for treatment, thus eliminating the return visit cost of $13.05 per patient. The program costs shown in Table 1 decreased by 8.6% to 9.4%, but the rank order remained the same: Test/Co-Treat had the highest program cost of the three algorithms, Test was second, and Co-Treat had the lowest program cost (results not shown).
Sensitivity Analysis Results
The sensitivity analysis results are confined to net costs because the Test algorithm invariably prevented more cases of PID than Co-Treat, and the Test/Co-Treat algorithm prevented more cases of PID than Test.
First, we simultaneously varied the prevalences of C trachomatis, N gonorrhoeae, and coinfection over the ranges in Table 1, keeping all other variables at their baseline values. Figure 2 shows the algorithms with the lowest net costs at varying rates of C trachomatis prevalence and coinfection when the gonorrhea prevalence was at the lower end (1%;Figure 2A) and at the top end (10%;Figure 2B) of the sensitivity analysis range. The results shown in Figure 2 were calculated with use of the nucleic acid hybridization assay for C trachomatis and culture for N gonorrhoeae. The results were similar to those shown in Figure 2 when other testing combinations for C trachomatis and N gonorrhoeae were analyzed (data not shown). When the gonorrhea prevalence was 1%, one of the two algorithms involving C trachomatis testing (Test or Test/Co-Treat) had a lower net cost than the Co-Treat algorithm, as long as the prevalence of C trachomatis infection was higher than approximately 6.75%. When the gonorrhea prevalence was 10%, one of the two algorithms involving C trachomatis testing had a lower net cost than the Co-Treat algorithm, as long as the prevalence of C trachomatis infection was >10.5%. Above these chlamydial infection prevalences, one of the algorithms including testing for C trachomatis was always less costly than the Co-Treat algorithm, regardless of the level of coinfection. In other words, with prevalences above these for C trachomatis infection, testing for C trachomatis is less costly than failing to test for it (when net costs are considered).
Second, we varied C trachomatis test costs over the ranges in Table 1, holding all other variables to their baseline values. As the prevalence of C trachomatis infection increased, the threshold test cost increased. Above the threshold test cost, the Co-Treat algorithm had the lowest net cost; below the threshold test cost, either the Test or Test/Co-Treat algorithm had a net cost that was lower than that of the Co-Treat algorithm. For example, when the gonorrhea prevalence and coinfection rates were held to their baseline values, the test used for N gonorrhoeae was culture, and the test used for C trachomatis was the nucleic acid hybridization assay, the threshold C trachomatis test cost increased from $5.91 to $8.87 when the chlamydial infection prevalence increased from 8% to 12%. At the lowest value of the range of the sensitivity analysis for C trachomatis test cost, $3.95, the threshold chlamydial infection prevalence was 6%. When the C trachomatis prevalence of infection exceeded 6%, one of the algorithms calling for C trachomatis testing had a lower net cost than Co-Treat.
We repeated this sensitivity analysis for the C trachomatis nucleic acid amplification assay. The nucleic acid amplification assay for C trachomatis was more sensitive but also more costly than the nucleic hybridization assay. Therefore, the Co-Treat algorithm had the lowest net cost unless the chlamydial infection prevalence exceeded 12% at the baseline test cost of $10.18. This was true regardless of which test was used for N gonorrhoeae.
Varying the cost per case of PID had a large impact on net cost and on the differences in net cost between the algorithms. If we used a cost per case of PID of $2780, 29 the Test/Co-Treat algorithm was the lowest-cost option for all chlamydial infection rates and coinfection rates examined, except when the prevalence of N gonorrhoeae infection was 8% or higher. This was true at all C trachomatis and coinfection rates examined. The Test/Co-Treat algorithm had the lowest net cost for virtually all N gonorrhoeae, C trachomatis, and coinfection rates when the PID cost per case exceeded $3500.
The Test/Co-Treat algorithm was a cost-effective option even if compared to the Test algorithm as an alternate. Figure 2 shows that the Test/Co-Treat algorithm had a lower expected cost than the Test algorithm when the coinfection rate was >17% (Figure 2A) or >10.5% (Figure 2B). The coinfection rate at which the Test/Co-Treat algorithm's net cost was lower than that of the Test algorithm decreased as the prevalence of either chlamydial infection or gonorrhea rose.
Current CDC treatment guidelines for dual therapy for gonococcal and chlamydial infections focus on the prevalence of C trachomatis coinfection among patients with gonorrhea. A relatively high prevalence of N gonorrhoeae infection is often found among STD clinic and hospital emergency room patients, jail and prison inmates, and other populations, but in many settings, such as among family planning clinic patients, the prevalence of gonorrhea is typically both low and lower than the prevalence of chlamydial infection, although the coinfection rate is often in or above the range of 20% to 40% suggested in the 1998 CDC guidelines. 30 Our analysis indicates that in such settings, the decision of which algorithm to use should be based upon the prevalence of chlamydial infection, not the coinfection rate.
The prevalence of gonorrhea will be lower than the prevalence of chlamydial infection in most instances. Even if the coinfection rate is high, the majority of women infected with C trachomatis will not be treated if the treatment decision is based on the outcome of a test for N gonorrhoeae. As the prevalence of chlamydial infection rises, the cost of failing to identify and treat women who are infected with only C trachomatis rises as well. As the prevalence of N gonorrhoeae increases, the coinfection rate becomes a stronger determinant of the cost-effectiveness of dual therapy. However, it does so only at prevalences of N gonorrhoeae infection that are at or beyond what prevails in many populations. For example, if the gonorrhea prevalence is 8%, the chlamydial infection prevalence is 10%, and the coinfection rate is 50%, then 40% of the patients infected with C trachomatis would receive treatment through the application of the Co-Treat algorithm. In such a setting, the cost of the Co-Treat algorithm may be lower than that of either the Test or Test/Co-Treat algorithm, even though the Co-Treat algorithm would avert fewer cases of PID than either of the other two algorithms. However, if the coinfection rate drops to 30%, then only 24% of the patients infected with C trachomatis would receive treatment under the Co-Treat algorithm, making it both substantially less effective and higher in net cost than the other two algorithms.
Because the Test algorithm will lead to the treatment of more chlamydial infections than the Co-Treat algorithm in virtually any population, it is likely that the choice of which algorithm to use will be based primarily upon cost. Our analysis shows that in settings where the Test algorithm is determined to be cost-effective, the Test/Co-Treat algorithm usually will be, as well, except in populations that have very low coinfection rates. The additional reduction in cases of PID resulting from applying the Test/Co-Treat algorithm in comparison to the Test algorithm is relatively limited, but it may be large enough to more than compensate for the small additional treatment cost. This indicates that dual treatment might be a cost-effective option if coupled with testing for C trachomatis but that it is a poor substitute for testing for C trachomatis in most instances. However, it will also lead to a greater degree of overtreatment.
Given the rates of coinfection typical in most US populations, most patients receiving therapy for C trachomatis infection under a dual-treatment algorithm will not actually be infected with C trachomatis. Overtreatment may promote antimicrobial resistance or decreased susceptibility of both N gonorrhoeae and C trachomatis. 12–15 Thus, in settings where strains of C trachomatis are resistant to or have decreased susceptibility to doxycycline or azithromycin, the Test algorithm, which uses testing for C trachomatis to guide treatment, may be more appropriate. Alternatively, it is also possible that routine dual treatment may hinder the development of resistant strains of N gonorrhoeae. 2 We also considered a fourth algorithm, one in which patients would be tested only for C trachomatis and in which treatment for both N gonorrhoeae and C trachomatis would be given to women with a positive test result, but we did not present the results because it offered no clear net-cost advantage and resulted in significant overtreatment against N gonorrhoeae.
Our analysis was sensitive to changes in PID and testing costs. Higher PID costs make the algorithms requiring C trachomatis testing become relatively more cost-effective. Thus, in settings where PID costs tend to be high because PID is treated by emergency departments rather than in primary care outpatient settings (e.g., as is often the case with uninsured populations), the algorithms requiring C trachomatis testing will be more cost-effective or cost-saving than suggested by Table 2. Similarly, increasing test costs make the algorithms requiring additional testing relatively more expensive. This may constitute a barrier to individual providers who may pay higher test costs, such as in private sector settings with low patient volume that cannot negotiate lower test costs. Conversely, our analysis was relatively insensitive to treatment costs.
This analysis was conducted from a healthcare system perspective. The results would be much different if the analysis was done from the perspective of an individual provider that cares for acute infections but may not realize savings from averted PID that can develop months to years later. Although the algorithms requiring testing for C trachomatis avert more PID, they are most costly to implement, especially when test costs are high. The program cost column of Table 2 shows the cost differences between the different algorithms when ignoring PID costs and including only testing and treatment costs. This difference is more marked at the upper end of the range of test costs provided in Table 1. At the highest test costs, the program cost difference between these algorithms would be nearly $30 per woman screened. In many settings where women may be in continuous care for several years after an acute C trachomatis or N gonorrhoeae infection, an individual provider may bear some of the costs of PID if the acute infection is not treated. However, because approximately 72% of the expected cost per case of PID is attributable to acute PID 27 rather than to the sequelae of chronic pelvic pain, ectopic pregnancy, and infertility—which can occur long after the initial episode of PID 11 —a woman need not be in continuous care for substantial savings of averted PID to be realized.
The effectiveness and cost of an algorithm are only some of the factors that should be considered when choosing the most appropriate algorithm for a given clinical setting; operational factors are also important. When asymptomatic women present for care, a decision is made at the time of the initial visit whether to test for both C trachomatis and N gonorrhoeae. If women are initially tested only for N gonorrhoeae, by the time the test results are available, it is inconvenient or impractical to recall women with negative test results for a subsequent test for C trachomatis. An alternative approach could involve collecting two specimens initially and processing the specimen for C trachomatis testing only if the specimen for N gonorrhoeae testing was negative. This sequential testing algorithm, coupled with co-treatment of women testing positive for N gonorrhoeae, would be effective in treating women infected with C trachomatis and could prove to be the lowest cost in almost every setting. However, it would impose additional treatment delays because of the need to process the tests sequentially rather than simultaneously. Adopting a policy of testing women for both infections at the outset can be cost-effective and can be cost-saving if the C trachomatis prevalence among asymptomatic women exceeds relatively modest levels (as low as approximately 6%).
This study has several limitations. First, the published range of values for the probability that gonorrhea or chlamydial infection will result in PID and subsequent sequelae is wide (from 10% to 40%). 11,20,31,32 In this analysis, we have relied on lower estimates of progression to sequelae; if, however, rates of progression to sequelae were higher, then the value of adopting an algorithm involving C trachomatis testing would increase, and the prevalence of C trachomatis infection at which screening is cost-effective would fall.
Second, our model did not consider the effect of transmission to sex partners or continued transmission to others within a sexual network. As more patients and their sex partners are cured of their infections, fewer cases of reinfection will occur, thus decreasing the clinical burden and costs of PID and subsequent sequelae. Incorporating this into the model would increase the benefit of C trachomatis treatment and would make the Test and Test/Co-Treat algorithms more cost-effective in comparison with the Co-Treat algorithm than they appear in Table 2. Conversely, the value of treatment may be overstated if a patient is rapidly reinfected because partners are not also treated.
Third, we did not consider neonatal complications in this analysis. From 30% to 40% of infants born to mothers with untreated chlamydial infection during pregnancy will develop neonatal conjunctivitis, and up to 22% will develop pneumonia. 33–36 Complications of untreated gonococcal infection in the neonate include conjunctivitis, ophthalmia, arthritis, and adverse pregnancy outcomes. 37 This would also increase the benefit of treatment against C trachomatis and N gonorrhoeae and would make the algorithms involving C trachomatis testing more cost-effective than they presently appear (Table 2).
Taken together, these limitations likely understate the cost-effectiveness of testing for C trachomatis in comparison with dual treatment against C trachomatis and N gonorrhoeae without testing for C trachomatis. Given this, relying on routine dual treatment instead of testing for C trachomatis when the rate of coinfection exceeds 20% is probably less cost-effective than we have observed here. It is also less effective at preventing PID in women, regardless of the coinfection rate.
Dual treatment serves a role and is cost-saving when the coinfection rate is sufficiently high, but our findings indicate that the precise threshold is dependent on the underlying prevalence of C trachomatis and N gonorrhoeae and in virtually all settings is lower than the coinfection rate of 20% suggested in the current guidelines.
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