Probability of a false-negative HIV antibody test result during the window period: a tool for pre- and post-test counselling

Abstract

Failure to understand the risk of false-negative HIV test results during the window period results in anxiety. Patients typically want accurate test results as soon as possible while clinicians prefer to wait until the probability of a false-negative is virtually nil. This review summarizes the median window periods for third-generation antibody and fourth-generation HIV tests and provides the probability of a false-negative result for various days post-exposure. Data were extracted from published seroconversion panels. A 10-day eclipse period was used to estimate days from infection to first detection of HIV RNA. Median (interquartile range) days to seroconversion were calculated and probabilities of a false-negative result at various time periods post-exposure are reported. The median (interquartile range) window period for third-generation tests was 22 days (19–25) and 18 days (16–24) for fourth-generation tests. The probability of a false-negative result is 0.01 at 80 days’ post-exposure for third-generation tests and at 42 days for fourth-generation tests. The table of probabilities of falsely-negative HIV test results may be useful during pre- and post-test HIV counselling to inform co-decision making regarding the ideal time to test for HIV.

Keywords

HIV AIDS diagnosis testing seroconversion HIV assays window period eclipse period false-negative

Background

Over 34 million people worldwide are estimated to be living with HIV infection.¹ Detection of acute HIV is key to reducing onward transmission as individuals are most infectious at this phase.² Moreover, individuals who are unaware of their HIV status have been shown to disproportionately contribute to onward transmission.³ HIV test technologies, including assays that detect viral RNA, p24 antigen, HIV antibodies and antibody/antigen in combination are beneficial in that, collectively, they diagnose HIV in acute and latent phases. However, clinicians face challenges when they attempt to provide accurate estimates of window periods (WPs), i.e., the time between the infection and first detection of HIV,⁴ during pre- and post-test counseling with clients. For antibody-based tests, the WP is the time to first detection of antibodies and leads to full seroconversion, which is the serological confirmation of HIV infection following a prior negative test. Time from infection to the appearance of antibodies varies among individuals,⁵ and while seroconversion demonstrates a final diagnosis of HIV, markers of infection such as RNA and p24 antigen appear earlier. Figure 1 illustrates the appearance of these markers leading up to seroconversion.

Figure 1.

Time to detection of HIV RNA, p24 antigen and antibody via various HIV assays.

Early diagnosis after HIV exposure has potential benefits to patients. Early treatment has been shown to improve long-term outcomes⁶ and can reduce the likelihood of onward transmission, especially if strategies, such as risk-behaviour counselling and/or early treatment to reduce viral load, can be rapidly implemented.⁷ There is a utilitarian public health benefit for adopting test technologies that provide accurate results with minimal WP; however, from a clinical perspective it has become increasing difficult to counsel clients about the optimal time to test after a risk event, especially when clients are anxious to know the earliest time they can test to confirm positivity, or the longest time they have to wait to know with a fair degree of certainty that they are indeed HIV-negative.

Research has shown that pre-test anxiety is high for a large percentage of individuals testing for HIV which, in some cases, results in denial of risk and test avoidance.⁸ When these individuals decide to test, recommendations to “wait out” the WP can create further anxiety related to fear of a positive result and the accompanying HIV-related stigma.^8–13 People use the words ‘nerve-wracking,’ ‘constant fear’, and ‘paranoid’ to describe their feelings while waiting for results¹³ or while waiting for the ‘appropriate’ time to present for a test, even for people with low risk. Some people value the time between the blood draw and receipt of results because it allows them time to prepare for the outcome, but research has also shown that HIV testers are primarily concerned about speedy and accurate test results.^8,12 Moreover, client anxiety is magnified with the ambiguity of an unconfirmed result caused by falsely-reactive screen tests and/or indeterminate Western blot (WB) tests. An indeterminate result occurs when a reactive third- or fourth-generation test fails to be confirmed by a WB test or when persons are in the process of HIV seroconversion. False antibody test reactivity usually results from antibodies binding to non-HIV components of the screening tests. The frequency of false-positivity may range from 0.03 in a low incidence setting such as China to 0.20 in an American low incidence population¹⁴ to 14% in high incidence settings in Africa.¹⁵ Supplemental tests conducted with a new blood sample are recommended to confirm the diagnosis.¹⁶ Indeterminate results that occur during early seroconversion are usually resolved with follow-up WB and/or HIV RNA testing. Follow-up testing will also be required if the individual tests non-reactive, but is within the WP for the screening test.¹⁷ Inconsistent information is often delivered to patients with indeterminate results, raising even further angst.^12,18 Thus, it is incumbent upon clinicians to be able to provide accurate information about the probability of an accurate test result given an estimated date of exposure.

Determining the WP length, which varies due to the dynamic and heterogeneous nature of viral and host responses, has preoccupied researchers for decades.^2,19–24 Busch et al.² identified six major elements relevant to determining WP lengths: (1) patients with symptoms of acute HIV infection, (2) patients with primary HIV infection with a known date of exposure, (3) recipients of infected blood products, (4) seroconverting plasma donors who provide serial blood samples, (5) serial blood samples from high-risk cohort studies and (6) animal models. The current literature reports average WPs (variances are rarely provided) or ranges of days after infection that any given assay will detect HIV infection.²⁴ Seroconversion panels from plasma donors are likely the most informative source of WP data for different tests, due to the frequency of specimen collection before and after HIV RNA is identified during screening, often at Fiebig Stage I.²⁵ The number of days from infection to detection of viraemia is known as the eclipse phase and is crucial to calculating an assay’s overall WP. Markov models have been used to describe the progress through the various stages of HIV in an infected person.^25–27 Markov modelling examines a collection of states (like various stages of HIV infection) and determines how HIV infection transitions from the state of eclipse period state through to the state to the latent infection state, given statistical information about the way that these state transitions are set up.²⁸ Modeling has estimated the eclipse period to be 10 days in duration.²

The purpose of our study was to use knowledge of the eclipse period and data from commercial and literature-reported seroconversion panels to calculate the WPs for third- and fourth-generation HIV tests and to provide a table reflecting the probability of a negative test result during the WP among known HIV-infected individuals.

Methods

Third- and fourth-generation HIV test data were extracted from publicly available data sheets from HIV-positive seroconversion reference panels from Boston Biomedica Inc/Seracare (BBI) (West Bridgewater, MA) dated April 1981–October 2006²⁹ and ZeptoMetrix Corporation (Buffalo New York) dated May 1996–December 2006.³⁰ These manufacturer panels include third-generation antibody, fourth-generation antigen/antibody, p24 antigen, polymerase chain reaction (PCR), and WB results from serial bleeds of plasma donors on repeated days before and after seroconversion. Each panel represents data from one HIV-infected individual and consists of results from a variety of assays. Panels were included in our analysis only if they provided a third-generation or fourth-generation test result and a PCR test result, and are currently in use for HIV diagnosis. Results of rapid point-of-care tests were excluded from the analysis.

Manuscripts with seroconversion data not already included in the BBI and ZeptoMetric panels were identified by a systematic review of the literature. We searched Medline and Embase databases for articles published between 1990 and 2010. Both databases were searched using the following terms: HIV infection; HIV diagnosis; HIV screening; immunoassay; HIV diagnostic test; serology; nucleic acid assay; nucleic acid amplification test (NAAT); HIV antibody tests; enzyme-linked immunosorbent assay; enzyme immunoassay (EIA); PCR; western blot; HIV-negative; acute infection; WP; reverse transcription (RT)-PCR amplification assay; pooled HIV RNA; HIV RNA; HIV NAAT; NAAT; HIV NAT; NAT; diagnostic tests, diagnostic testing, and screening. Titles and abstracts were reviewed by two reviewers (DT and MD) to determine if they should be included in the analysis, duplicates were removed and data including date of last negative and date of first positive for third-generation fourth-generation and PCR/NAAT tests were extracted.

Third- and fourth-generation test results are typically expressed as signal to cutoff (s/co) ratios. Ratios ≥1.0 are considered reactive. The date of each blood draw, associated s/co (or positive/negative status) and name of assay were extracted for each donor. The number of days between blood draws was calculated and the date of first positive PCR/NAAT test for each assay was noted. The number of days from the positive PCR/NAAT test to the first positive third- or fourth-generation test for each panel was calculated, and added to an estimated eclipse period to represent the number of days from infection to first positive third- or fourth-generation results.

In order to estimate the eclipse period, which is the time from infection to detection of virus by PCR/NAAT test, the information assembled by this systematic review was used to parameterize a stochastic model of early HIV infection.³¹ This new methodology, based on a continuous time branching process of infection, conditioned on survival of the virus, allows the duration of the HIV WP to be estimated subject to a small number of well-defined assumptions. The model confirms the widely held hypothesis that typical eclipse periods are in the range of 8–14 days, consistent with Fiebig’s estimate of 10 days.³² Therefore, we used an eclipse period of 10 days to calculate the probability of a negative test at a given time post-exposure in an HIV-positive individual. WPs for each third-generation and fourth-generation HIV assay were calculated as follows: 10 days + number of days between the first positive PCR test and the first positive third- or fourth-generation test.

Frequency analysis was conducted to describe the estimated WP for both third- and fourth-generation tests. These data were then used to draw a Kaplan-Meier curve and the cumulative proportion of tests remaining negative was used to calculate the conditional probability of a negative test result at various time intervals.

The study received ethical approval from the University of British Columbia Clinical Research Ethics Board (H11-01197).

Results

Third-generation antibody tests

Data from 136 seroconversion panels were identified consisting of 1361 individual assay results. A total of 780 individual assay results were excluded because they did not have both a PCR and third-generation results (n = 436), they used an assay that was no longer in routine use (n = 61), the donor did not seroconvert prior to cessation of donating plasma (n = 49), the length of time between blood draws resulted in the PCR being positive on the same day as the antibody test (n = 41), and duplicate records (n = 193). Panels that had the same panel ID number, the same assay and the same manufacturer were considered duplicates. Figure 2 displays the number of individual assay results included and excluded for panels provided by manufacturers and panels that were retrieved from the literature. Due to the anonymous nature of the samples, no demographic or risk factor information is known.

Figure 2.

The number of individual assay results included and excluded for panels provided by manufacturers and panels that were retrieved from the literature.

WPs ranged from 12 to 99 days. Overall the mean (SD) WP for all assays is 25.04 (13.1) days (manufacturer: 22.16 [7.1]; literature: 26.68 [16.9]). The median WP is 22 days (interquartile range [IQR]: 19–25) (manufacturer: 21; IQR: 19–24); literature: 24; IQR: 19–28). Table 1 displays the probability of a negative test result for a third-generation HIV test at various time points in an HIV-positive individual. Figure 3 displays the distribution of WP days for third-generation EIA tests. Figure 4 displays time to seroconversion using a Kaplan-Meier curve.

Figure 3.

The distribution of WP days for third-generation antibody tests.

Figure 4.

Time to seroconversion for third- and fourth-generation tests using a Kaplan-Meier curve.

Table 1.

Probability of a negative test result for a third- and fourth-generation HIV test at various time points in an HIV-positive individual.

Time since infection (days)	Cumulative conditional probability (99% confidence interval)
Time since infection (days)	Third generation		Fourth generation
0–9	1.00	(.991–1.00)	1.00	(.992–1.00)
10	1.00	(.991–1.00)	0.99	(.968–.993)
12	0.99	(.971–.996)	0.86	(.820–.890)
14	0.95	(.920–.968)	0.79	(.748–.829)
16	0.80	(.751–.837)	0.51	(.463–.562)
18	0.70	(.650–.747)	0.40	(.356–.453)
20	0.56	(.503–.609)	0.35	(.305–.400)
22	0.46	(.403–.509)	0.31	(.264–.355)
24	0.23	(.187–.277)	0.20	(.159–.238)
26	0.22	(.174–.262)	0.18	(.141–.216)
28	0.13	(.097–.169)	0.08	(.058–.113)
30	0.09	(.062–.122)	0.08	(.054–.108)
32	0.09	(.062–.122)	0.07	(.048–.099)
34	0.07	(.049–.104)	0.05	(.034–.078)
40	0.05	(.038–.088)	0.05	(.034–.078)
42	0.05	(.038–.088)	0.01	(.005–.027)
45	0.05	(.038–.088)	0.01	(.005–.027)
50	0.05	(.028–.074)	0.00^a	0
55	0.04	(.026–.070)
60	0.04	(.020–.061)
65	0.04	(.020–.061)
70	0.03	(.014–.050)
75	0.03	(.014–.050)
80	0.03	(.014–.050)
85	0.01	(.002–.022)
90	0.01	(.002–.022)
95	0.01	(.002–.022)
99	0.00^a	0

These numbers are based on a sample of seroconversion panels. However, theoretically, the probability of a negative test result in an HIV-positive person never reaches zero.

Fourth-generation antibody/antigen tests

Data from 211 seroconversion panels were identified consisting of 1229 individual assay results. A total of 569 individual assay results were excluded because they did not have both a PCR and a fourth-generation test result (n = 415), they used an assay that was no longer in routine use (n = 6), the donor did not seroconvert prior to cessation of donating plasma (n = 21), and the length of time between blood draws resulted in the PCR being positive on the same day (n = 127). Figure 5 displays the number of individual assay results included and excluded for panels provided by a manufacturer and panels that were retrieved from the literature.

Figure 5.

The number of individual fourth-generation results included and excluded for panels provided by a manufacturer and panels that were retrieved from the literature.

WPs ranged from 11 to 43 days. Overall the mean (SD) WP for all assays is 20.45 (7.0) days (manufacturer: 18.4 [4.0]; literature: 20.76 [7.2]). The median WP is 18 days (IQR: 16–24) (manufacturer: 17, IQR: 16–20.5; literature: 18, IQR: 16–25). Table 1 displays the conditional probability of a negative test result in an HIV-positive individual for a third- and fourth-generation HIV test at various time points following an HIV exposure. Figure 4 displays Kaplan-Meier curves with the time to seroconversion based on a third- and fourth-generation anti-HIV assays. Figure 6 displays the distribution of WP days for fourth-generation tests.

Figure 6.

The distribution of WP days for fourth-generation tests.

Discussion

This study provides estimates for the probability of a false-negative third- and/or fourth-generation EIA HIV test at various time intervals after HIV infection. The overall median WPs (22 days for third generation; 18 for fourth generation) are consistent with what others have reported, mainly through mathematical modeling which estimates the eclipse period.^2,33,34 Other studies using dates from the onset of seroconversion illness symptoms report that third-generation assays become positive approximately 13 days after the onset of symptoms with fourth-generation tests becoming positive in as little as two days after symptom onset.³⁵ However, these studies do not take into consideration the eclipse period prior to the onset of symptoms which can be 1–2 weeks.³⁶ In addition, studies examining the WP from recipients of HIV-infected blood products report a two-week eclipse period.³⁷

The reported mean/median WPs for third- and fourth-generation tests vary. Older studies of third-generation tests estimated WPs of 45 days.³⁸ The 23-day reduction in the WP to 22 days likely reflects improvements in the selection of HIV antigen targets as well as improvements in antibody test signal amplification chemistries. However, it may also be due to the methods and assumptions used to determine the actual date of seroconversion. Many researchers model estimates of the date of seroconversion using the date of last negative and positive test under the assumption that the data are normally distributed. However, our analysis suggests that the time to seroconversion between blood draws is not normally distributed, in part because there is an eclipse phase prior to which HIV RNA is not detected and during this time period, the antibody response is not typically elicited. Therefore, we have used a median value which likely provides a more accurate estimate of the WPs. The median WP for the fourth-generation assays was four days shorter than the third-generation assays which results from the detection of p24 by the fourth-generation assay and is consistent with earlier findings.^2,39–42

We have combined information from previous mathematical modelling of data from known seroconverters to not only confirm median WPs reported by others, but also to provide the probability of a false-negative test result at various points after exposure, which may be useful in pre- and post-test counselling. For example, if a patient requests an HIV test 16 days after a high-risk sexual encounter (e.g., unprotected anal intercourse), by using our instrument, a clinician might advise the person that if they are indeed infected there is an 80% chance a third-generation test would be negative or a 51% chance that a fourth-generation test would be negative if they had, in fact, become infected. In contrast, the clinician can advise that after 99 days, a third-generation test has essentially a 0% chance of giving a false negative result or after 50 days for a fourth-generation test. This is the first time, to our knowledge, that such information has been reported. However, clinicians using this instrument should understand that these probabilities do not take into account inter-patient variability in the length of the eclipse phase and the antibody response. Mathematical modelling based on the data presented here suggests that the majority of patients have an eclipse phase duration in the range of 6–16 days, encompassing the simple estimate of 10 days that we used to construct the table of probabilities. However, it is entirely possible that a small number of patients will have atypical responses leading to much longer eclipse phases. This new pre-test counselling instrument may help reduce anxiety for clients and promote co-decision making with their health care provider regarding the best time to undergo testing for HIV.

Results of rapid point-of-care tests were excluded from analysis so we are unable to estimate the WPs for these assays. It is expected that rapid assay WPs are likely to be somewhat longer than for laboratory-based tests.^43,44 Clinicians who offer point-of-care tests to clients should include this potential limitation in their pre- and post-test counseling.

Limitations

This review synthesized data from third- and fourth-generation HIV tests conducted between 1981 and 2006. Current fourth-generation assays have likely improved since 2006 but it is not possible to determine what assay modifications may have been made by manufacturers over time, as this information is not reported. Specifically, the Abbott fourth-generation ARCHITECT HIV Ag/Ab Combo assay has been reported to identify HIV infection within two weeks⁴⁵ compared to the median of 18 days we reported. Practitioners who counsel patients who have been tested with a fourth-generation test should keep this in mind when using our table of probabilities.

It is important to recognize that WPs are estimates and that there is considerable individual variation with some individuals having shorter or longer than average WPs. Pollett et al.’s⁴⁶ example of a 21-month time-to seroconversion in a 30-year-old woman is an excellent example of how variable WPs can be. Therefore, practitioners using the table of probabilities to counsel their patients should do so with this caveat.¹⁷

The authors recognize that the instrument we report has not been clinically validated. Further research is required to confirm the validity and reproducibility of the instrument, as well as its acceptability to clinicians and clients. In addition, individuals who donated serum for the commercial seroconversion panels were paid donors. We do not know the socio-demographic characteristics of these donors, but it is possible that they may not be representative of the general population.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Canadian Institutes for Health Research [FRN: 108451].

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