From the Idaho Bureau of Laboratories, Department of Health and Welfare, Boise, ID
The authors thank Katey Anderson, Dr. Christopher L. Ball, Dr. David Fine, Colleen Greenwalt, and Steven J. Shapiro for their constructive comments on this article, and IBL CTNG support staff.
Supported in part by the Comprehensive STD Prevention Grant (CFDA Number 93.977), Centers for Disease Control and Prevention.
Correspondence: Joanna Lynn Lewis, BS, Idaho Bureau of Laboratories, Department of Health and Welfare, 2220 Old Penitentiary Road, Boise, ID 83712. E-mail: firstname.lastname@example.org.
Received for publication May 6, 2011, and accepted August 8, 2011.
Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG) are 2 of the most common sexually transmitted diseases (STD) in the United States and are major contributors in pelvic inflammatory disease. Most infections are asymptomatic and, if untreated, can lead to infertility, ectopic pregnancy, infant conjunctivitis, and pneumonia, and may increase the risk of acquiring HIV.1,2 The Centers for Disease Control and Prevention report more than 1.244 million cases of Chlamydia infections occurring annually in the United States, with nearly 50% in persons aged 15 to 24 years.3
Previous studies have shown that CT/NG specimen pooling is beneficial for high-throughput testing in low-prevalence (≤8%) populations.4–8 In addition to prevalence, specimen pooling efficiency and accuracy are affected by pool size and the distribution of positive specimens within pools.5–7,9,10 The Idaho Bureau of Laboratories (IBL) tests approximately 15,000 CT/NG specimens annually with 8.15% prevalence for CT and 0.56% for NG (Idaho Bureau of Laboratories, unpublished data 2009), making CT/NG testing at IBL a prime candidate to realize efficiency through an optimized pooling strategy. This study demonstrates that stratification of pool design using the Reason for Visit information available on the Region X/Infertility Prevention Project Submission Form (IPP form) results in optimized processing efficiency and additional cost savings over previously used pooling strategies.
Study specimens were selected from representative months for comparison. Due to sample volume similarity, comparable submission clients and data availability, July 2007 and July 2009 were selected. Specimens included urine, cervical, and urethral samples obtained from both men and women submitted for STD screening. Specimens were submitted from demographically and geographically diverse populations across Idaho. Examples of frequent submitters include public health district clinics (STD and Family Planning), county jails, juvenile detention centers, and college campuses. Only specimens submitted with the IPP form were included in this study. Through consultation, clinicians categorize a patient's Reason for Visit on the IPP form as: Exposed to CT/NG, Rescreening CT+ or NG+, Routine Visit, STD Screening, Symptoms, Exposed to Other STD, Pregnancy Test Only, or Follow-up post treatment. In instances where no reason was indicated on the submittal form, the specimen was classified as Not Provided.
Specimens received in July 2007 were pooled in groups of 4 chronologically, regardless of Reason for Visit. Retrospective evaluation of the 2007 IBL data suggested that specimens identified on the IPP form as Exposed to CT/NG or Rescreening CT+ or NG+ appeared to be at higher risk of testing positive and should be excluded from pooling. This exclusion of high-risk samples followed by pooling of remaining (low-risk) samples formed the basis of the IBL stratified specimen pooling (SSP) scheme (Fig. 1). Specimens received in July 2009 were stratified by Reason for Visit criteria and then placed into pools of 4. Regardless of pooling strategy (chronological or SSP), specimens that could not be assembled into pools of 4 were placed into pools of 2 or 3 or tested individually to ensure that all specimens received in one day would be tested together. These “test individually for convenience” samples constituted a very small proportion of samples tested each month (Fig. 1).
Samples were analyzed using the Gen-Probe Aptima Combo 2 Assay nucleic acid amplification test (NAAT) (Gen-Probe, San Diego, CA), according to manufacturer's instructions.11 All specimens were aliquoted in the following manner using the TECAN DTS robot before beginning testing. Individually tested samples: 400 μL of each specimen was removed from the collection tube and transferred to a reaction tube. Pooled Samples: 100 μL from each of 4 original specimens was transferred into 1 reaction tube to form a pool with a total volume of 400 μL. Pools of 3 (300 μL) and 2 (200 μL) were also aliquoted via the TECAN, but volumes were adjusted manually to meet the minimum volume requirement of ≥300 μL. Each pooled set of specimens were analyzed, and those that showed positive signals were individually tested the next day to determine the positive specimen(s). Pools with a negative result were not tested further. Infrequently, all of the individual samples from a positive pool tested negative during follow-up. These samples required additional analysis. Most specimens were reported as equivocal or negative after resolution (Fig. 1).
Data were compiled and analyzed in MS Excel. Testing statistics were calculated using CT/NG testing records for each study period. Reason for Visit information was obtained from the original IPP forms. Percent (%) positivity for each reason code was calculated using the CT/NG testing records and the Reason for Visit data. Z-tests were performed to assess significance (P < 0.05) using SigmaPlot 11 (Systat Inc., San Jose, CA). Estimates of laboratory direct costs were calculated for each pooling approach and compared with the cost of testing all samples individually within each of the study periods. Cost savings were calculated based on an IBL Aptima Combo 2 cost analysis (Idaho Bureau of Laboratories, unpublished data 2010). The direct cost, factoring reagents, consumables, and technologist time, was calculated as US$14.47 for each individual test.
Analysis of the positivity rates for each Reason for Visit category is detailed in Table 1. Data compared between the 2 representative months showed that Exposed to CT/NG and Rescreening CT+ or NG+ categories had comparatively higher positivity rates than the remaining categories. The Routine Visit, STD Screening, and Symptoms categories proved to be the 3 most commonly selected reasons with the highest volume of submissions; and thus were the most appropriate candidates for specimen stratification and pooling. Samples in the Pregnancy Test Only and Not Provided categories were considered lower risk and pooled with Routine samples to create pools of 4 (Fig. 1).
The use of SSP resulted in a drop in the positivity of pools, reduced number of repeat tests, and realized substantial cost savings compared with chronological pooling and testing all samples individually. A total of 1509 specimens were received for CT/NG analysis during July 2007 (Table 2). At this time, samples received by IBL were processed using the chronological pooling method. In July of 2009, there were a total of 1381 samples received for analysis using the SSP method of pooling. By removing Exposed to CT/NG, Retesting CT/NG specimens and pooling those from Routine, STD Screening, and Symptoms categories, the proportion of positive pools dropped by 7% from 29.8% in July 2007 to 22.8% in July 2009 (z-test, P = 0.044, SigmaPlot 11) (Table 2). The percentage of samples requiring repeat testing dropped from 31.9% to 22.7%, reducing the number of tests performed in July 2009 by 9.2% (z-test, P ≤0.001, SigmaPlot 11) (Table 2).
Cost savings were estimated using the number of specimens received and the number of tests performed (Table 2) for each study period and multiplying each by $14.47 (IBL direct cost per sample). The estimated cost to test all samples (no pooling) for July 2007 was $21,835. The cost of pooled tests performed using chronological pooling was $12,675. The estimated cost to test all samples in July 2009 (no pooling) was $19,983. The cost of pooled tests performed using SSP was $10,519. Calculated cost savings between pooling strategies were significant (z-test, P = 0.003, SigmaPlot 11), increasing from 41.9% in July 2007 to 47.4% in July 2009. Using SSP for pool design saved approximately $2156 per month in laboratory direct costs by dropping the direct cost per sample from $14.47 to $8.24. This allowed for the testing of 15,211 specimens for the price of 8666 specimens (Idaho Bureau of Laboratories, unpublished data 2010).
Nationally and in Idaho, CT rates are on the rise. Idaho CT prevalence increased from 7.7% in 2007 to 8.2% in 2009 (Idaho Bureau of Laboratories, unpublished data 2007, 2009). SSP has allowed IBL to maintain efficiency by reducing the prevalence in the main pooling population; an important factor that is well supported by other pooling research.4,6–8,10–12 In addition, cost savings gained through SSP were similar to other studies,6,8,9,10 despite IBL's higher prevalence and smaller pool size. At present, TX is using a similar pooling method for NAAT HIV testing; separating high- and low-risk specimens based on patient risk factors and submitted client information.13
IBL observed little impact on personnel resources when implementing SSP, thus it is an easy and advantageous strategy for cost savings. IBL is considering the potential SSP compatibility with a TIGRIS or Panther system (Gen-Probe, San Diego, CA) as the samples are pooled via the TECAN before the testing begins. The use of an automated system would increase material cost per sample, but this may be offset by the reduction in technician time.
Data limitations: At the time of SSP implementation, Pregnancy and Not Provided were considered low risk. Because of the relatively small number of samples received in these categories and the observed higher prevalence (Table 1), future adjustments to the stratification strategy may be necessary for full optimization. Errors or bias may result from IPP Reason for Visit data being patient-reported and certain reasons possibly being underrepresented.
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