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.

Full text

Review article
Probability of a false-negative HIV
antibody test result during the window
period: a tool for pre- and post-test
counselling
Darlene Taylor
1,2
, Monica Durigon
1
, Heather Davis
3
,
Chris Archibald
4
, Bernhard Konrad
2
, Daniel Coombs
2
,
Mark Gilbert
1,2
, Darrel Cook
1,5
, Mel Krajden
1,5,6
, Tom Wong
3
and Gina Ogilvie
1,7
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
Date received: 3 March 2014; accepted: 9 June 2014
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 dispro-
portionately contribute to onward transmission.
3
HIV
test technologies, including assays that detect viral
RNA, p24 antigen, HIV antibodies and antibody/anti-
gen 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
1
British Columbia Centre for Disease Control, Vancouver, BC, Canada
2
School of Population and Public Health, University of British Columbia,
Vancouver, BC, Canada
3
Alberta Health Services, Edmonton, AB, Canada
4
Public Health Agency of Canada, Ottawa, ON, Canada
5
BCCDC Public Health Microbiology and Reference Laboratory,
Vancouver, BC, Canada
6
Pathology and Laboratory Medicine, University of British Columbia,
Vancouver, BC, Canada
7
Family Practice, University of British Columiba, Vancouver, BC, Canada
Corresponding author:
Darlene Taylor, BC Centre for Disease Control, 655 W12th Ave.,
Vancouver, BC V5Z 4R4, Canada.
Email: Darlene.taylor@bccd.ca
International Journal of STD & AIDS
2015, Vol. 26(4) 215–224
!The Author(s) 2014
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and while seroconversion demonstrates a final diagnosis
of HIV, markers of infection such as RNA and p24 anti-
gen appear earlier. Figure 1 illustrates the appearance of
these markers leading up to seroconversion.
Early diagnosis after HIV exposure has potential
benefits to patients. Early treatment has been shown
to improve long-term outcomes
6
and can reduce the
likelihood of onward transmission, especially if strate-
gies, such as risk-behaviour counselling and/or early
treatment to reduce viral load, can be rapidly imple-
mented.
7
There is a utilitarian public health benefit
for adopting test technologies that provide accurate
results with minimal WP; however, from a clinical per-
spective 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
Figure 1. Time to detection of HIV RNA, p24 antigen and antibody via various HIV assays.
216 International Journal of STD & AIDS 26(4)
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avoidance.
8
When these individuals decide to test, rec-
ommendations 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 results
13
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 pri-
marily concerned about speedy and accurate test
results.
8,12
Moreover, client anxiety is magnified with
the ambiguity of an unconfirmed result caused by fal-
sely-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 con-
firmed 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 inci-
dence population
14
to 14% in high incidence settings in
Africa.
15
Supplemental tests conducted with a new
blood sample are recommended to confirm the diagno-
sis.
16
Indeterminate results that occur during early sero-
conversion 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 indeter-
minate results, raising even further angst.
12,18
Thus,
it is incumbent upon clinicians to be able to pro-
vide 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 dec-
ades.
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 pri-
mary HIV infection with a known date of exposure, (3)
recipients of infected blood products, (4) seroconvert-
ing 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 speci-
men 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 tran-
sitions 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 litera-
ture-reported seroconversion panels to calculate the
WPs for third- and fourth-generation HIV tests and
to provide a table reflecting the probability of a nega-
tive 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 2006
29
and ZeptoMetrix Corporation (Buffalo New York)
dated May 1996–December 2006.
30
These manufac-
turer 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 iden-
tified 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 immuno-
assay (EIA); PCR; western blot; HIV-negative; acute
infection; WP; reverse transcription (RT)-PCR amplifi-
cation assay; pooled HIV RNA; HIV RNA; HIV
NAAT; NAAT; HIV NAT; NAT; diagnostic tests,
diagnostic testing, and screening. Titles and abstracts
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were reviewed by two reviewers (DT and MD) to deter-
mine if they should be included in the analysis, dupli-
cates 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 typic-
ally 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 system-
atic 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 dur-
ation 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
Figure 2. The number of individual assay results included and excluded for panels provided by manufacturers and panels that were
retrieved from the literature.
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fourth-generation HIV assay were calculated as fol-
lows: 10 days þnumber of days between the first posi-
tive 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 condi-
tional 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
(n¼436), they used an assay that was no longer in rou-
tine use (n¼61), the donor did not seroconvert prior to
cessation of donating plasma (n¼49), the length of
time between blood draws resulted in the PCR being
positive on the same day as the antibody test (n¼41),
and duplicate records (n¼193). Panels that had the
same panel ID number, the same assay and the same
manufacturer were considered duplicates. Figure 2 dis-
plays 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.
WPs ranged from 12 to 99 days. Overall the mean
(SD) WP for all assays is 25.04 (13.1) days (manufac-
turer: 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 dis-
plays the distribution of WP days for third-generation
EIA tests. Figure 4 displays time to seroconversion
using a Kaplan-Meier curve.
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 (n¼415), they used an assay that was no longer
in routine use (n¼6), the donor did not seroconvert
prior to cessation of donating plasma (n¼21), and
the length of time between blood draws resulted in
the PCR being positive on the same day (n¼127).
Figure 5 displays the number of individual assay results
included and excluded for panels provided by a manu-
facturer 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 (manufac-
turer: 18.4 [4.0]; literature: 20.76 [7.2]). The median
WP is 18 days (IQR: 16–24) (manufacturer: 17,
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)
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
a
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.
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Figure 4. Time to seroconversion for third- and fourth-generation tests using a Kaplan-Meier curve.
Figure 3. The distribution of WP days for third-generation antibody tests.
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IQR: 16–20.5; literature: 18, IQR: 16–25). Table 1 dis-
plays 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 fol-
lowing 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.
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 symp-
toms 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-gen-
eration tests estimated WPs of 45 days.
38
The 23-day
reduction in the WP to 22 days likely reflects improve-
ments in the selection of HIV antigen targets as well as
improvements in antibody test signal amplification che-
mistries. However, it may also be due to the methods
and assumptions used to determine the actual date of
seroconversion. Many researchers model estimates of
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.
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the date of seroconversion using the date of last nega-
tive 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 math-
ematical 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 inter-
course), 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 dur-
ation 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 pos-
sible 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
Figure 6. The distribution of WP days for fourth-generation tests.
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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 weeks
45
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.’s
46
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, prac-
titioners 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 char-
acteristics of these donors, but it is possible that they
may not be representative of the general population.
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 sup-
port 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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