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Draft Genetic Test Review Cystic
Fibrosis CLINICAL VALIDITY Question
18: How often is the test
positive when the disorder is present? Question 18: How often is the test positive when the disorder is present? Question 19: How often is the test negative when the disorder is not present? page 1 | page 2 | page 3 | page 4
Introduction ·
Clinical
sensitivity [ A / (A + C) ] is the proportion of couples in which both
partners are cystic fibrosis carriers (A+C) and who are correctly
identified as being positive (A) by the screening test.
·
Clinical
specificity [ D / (B + D) ] is the proportion of non-carrier couples (B+D)
who are correctly identified as being negative (D) by the screening
test. ·
Positive
predictive value [ A / (A + B) ] is the proportion of positive tests (A
+ B) that correctly identifies carrier couples (A).
·
Negative
predictive value [ D / (C + D) ] is the proportion of negative tests (C
+ D) that correctly identifies non carrier couples (D). Figure 1 shows an
example of applying prenatal screening for cystic fibrosis to a
hypothetical cohort of 1,000,000 couples.
In this example, the prevalence of cystic fibrosis is 1:2,500
(carrier rate 1/25), and the DNA test panel identifies 77 percent of the
carrier couples (if 88 percent of mutations are detectable in each
individual, then 88 percent squared, or 77 percent are detectable in the
couple). The analytic
sensitivity is taken to be 97.9 percent (Question 9), and the analytic
specificity (after confirmatory testing) is assumed to be, in this
example, 99.99 percent (false positive rate of 1 per 10,000 individuals
tested). Among the
population screened, there are 1,600 carrier couples (1,000,000 * (1/25)2).
77 percent of the 1,600 carrier couples are detectable (1,232),
and 1,181 of these are detected (1,232*.9792).
Among the 998,400 non-carrier couples, 76,800 will include one
carrier partner, and, in six of these couples, a false positive result
will occur in the non-carrier partner (76,800*.88*.979*0.0001).
The numbers from Figure 3-1 can now be entered into a two-by-two
table (Table 3-2) by substituting actual numbers into the format shown
earlier in Table 3-1. The
clinical performance estimates can then be computed.
Table 3-2. A Two-by-Two Contingency Table for Deriving the Four Major Clinical Performance Parameters in a Hypothetical Population of 1,000,000 Couples
Impact
of the screening model on these estimates Clinical
sensitivity Table
3-3. Clinical Sensitivity:
Proportion of Carrier Couples (or Affected Fetuses) Identified as a
Function of the Proportion of Cystic Fibrosis Mutations Detected by a
Given Screening Panel
Individual
mutation frequencies in the non-Hispanic Caucasian population In
order to estimate the proportion of carrier couples (or affected
fetuses) that can be identified for any given panel of mutations, it is
necessary to obtain the mutation frequencies in an unbiased sampling of
individuals clinically affected with cystic fibrosis.
Table 3-4 shows the frequencies of the 25 mutations in the panel
recommended for prenatal screening.
The table includes two studies of non-Hispanic Caucasians with
cystic fibrosis. The
mutations are listed in order of decreasing average frequency.
As an indicator of reliability of these mutation frequencies,
bolded entries indicate that the mutation was tested by more than
one-quarter of the laboratories (CF Consortium) and was observed more
than 10 times (CF Consortium and CF Foundation). Table
3-4. Mutation Frequencies
for non-Hispanic Caucasians in the United States Within the Recommended
25 Mutation Panel 1 Cystic Fibrosis Genetic Analysis Consortium (Kazazian, 1994), based on between 2,187 and 9,792 cystic fibrosis chromosomes (Appendix A) 2 A new analysis of the Cystic Fibrosis Foundation Patient Database, based on 3,938 chromosomes (Palomaki et al., 2002, – Appendix B) Mutation
frequencies derived from the Cystic Fibrosis Genetic Analysis Consortium
Report The summary estimate of 85.05 percent shown above from the
Cystic Fibrosis Genetic Analysis Consortium data is somewhat higher than
reported (Kazazian, 1994), because studies that reported mainly on
Hispanic, Ashkenazi Jewish or African American affected individuals are
removed from the present analysis.
Also, the denominators for each of the mutation frequencies are
computed in the present analysis by dividing the number of observed
chromosomes by the total number of chromosomes reported only for studies
that actually tested for the given mutation.
The earlier report (Kazazian, 1994) divided the observed number
of each mutation by the total number of chromosomes reported for all
studies. This oversight was
mentioned in the Kazazian report and has since been corrected (Giorgi et
al., 1997). For the
more common mutations, this second correction has little or no impact.
However, for the less common mutations, the corrected frequencies
will be higher than originally listed.
For example, the mutation frequency for A455E would be 0.28
percent prior to correction, and 0.54 percent after.
The entire reanalysis is contained in Appendix A, Table 3-14.
Additional information is available on-line (www.genet.sickkids.on.ca/cftr/newfreq/All.html),
but it is not clear whether blank entries on these newer tables indicate
“tested for and none found” or “not tested” (Markiewicz,
personal communication, 2001). For
this reason, they are not included.
The three mutations in the recommended panel (3120+1G>T,
2814delA and I148T) that were not part of
the Consortium’s report have been arbitrarily assigned a frequency of
0.10 percent (italics). There
are several limitations to using these data to estimate mutation
frequencies in the general population in the United States.
For example, it is not possible to determine to what extent these
studies included individuals who were Hispanic (or of other
racial/ethnic groups). Also,
some of the data reported to the consortium have been collected in
reference laboratories using mutation panels of 50 or more mutations.
It is possible that these expanded test panels were used
selectively in cystic fibrosis patients with less common mutations that
could not be identified by initial testing (e.g., the initial test may
have only analyzed delF508). A
major contributor to the consortium reports that this bias exists in its
data (Heim et al., 2001). Such a
bias will lead to under-estimation of the mutation frequency for
delF508. Another possible
bias might be the over-representation of some racial/ethnic groups. For example, if couples of Ashkenazi Jewish heritage were to
participate more fully in testing programs than other non-Hispanic
Caucasian couples, this would lead to an underestimation of the delF508
mutation frequency and an over-estimation of other mutations (e.g.,
W1282X). The present
analysis attempts to take this into account by removing any study from
the analysis if its population is mainly of Ashkenazi Jewish heritage. Mutation
frequencies derived from the Cystic Fibrosis Foundation Database
In an attempt to address the shortcomings of the Cystic
Fibrosis Consortium data, we undertook a reanalysis of the Cystic
Fibrosis Foundation Database. This
data source represents approximately 85 percent of all cystic fibrosis
patients in the United States. Previous
analyses have been applied to the entire collection of genotypes in that
database. This approach has strength in numbers (over 29,000
chromosomes studied), but it is not possible to document which mutations
have been tested for by the various contributing centers.
Thus, a small number of less common mutations might indicate a
low mutation frequency, but it might also indicate that few patients had
been tested for that mutation. This
issue is addressed here by focusing only on patients attending one of
nine Therapeutic Development Network (TDN) Centers that offer expanded
mutation panels to all patients. Previous
analyses of the Foundation’s data did not distinguish Hispanic from
non-Hispanic Caucasians. The
present analysis does. Of
the 2,507 self-declared Caucasian individuals with cystic fibrosis
attending a TDN center in 1999, 2,130 (85 percent) declared themselves
to be non-Hispanic, 302 (12 percent) did not answer (or were not asked)
the question, and the remaining 75 (3 percent) responded that they were
of Hispanic heritage. Of
the 2,130 non-Hispanic Caucasians eligible for analysis, 1,969 (92.4
percent) had been genotyped. The
remaining 7.6 percent either refused genotyping, or the results were not
yet available. The
Foundation's data do not allow separation of Ashkenazi Jewish
individuals from non-Hispanic Caucasians. When
comparing the mutation frequencies from the two sources shown in Table
3-4, the most striking difference is found in the estimate for delF508.
The estimate from the Consortium is nearly 7 percentage points
lower than the corrected estimate based on the Foundation’s data.
Based on biases that are likely to be present in the Consortium
data, the Foundation's estimate may be closer to the truth.
The total proportion of mutations identified from the Cystic
Fibrosis Foundation Patient Database is about 6.5 percentage points
higher than from the Consortium data.
This overall difference is mainly due to the variation in the
delF508 mutation frequency. Both
estimates are higher than initially reported (Kazazian, 1994) and than
generally quoted in the literature (Grody et al., 2001). The
following analyses use the averages of the mutation frequencies from the
two studies (Table 3-4). Table
3-5 shows the cumulative percentage of detectable mutations and the
carrier couple detection rate for 1, 5, 10, 15, 20 and 25 mutations. Mutations are added in the order shown in Table 3-4 and are,
therefore, only appropriate for non-Hispanic Caucasians.
Mutation frequencies in other racial/ethnic groups will be
considered later in this section. Figure 3-2 graphically displays the data shown in Table 3-5. Table 3-5. A Comparison of Mutation Panel Size and Percentage of Carrier Couples Detected, Assuming an Analytic Sensitivity of 100 percent
1 The order of added mutations is from Table 3-4
Prenatal cystic fibrosis screening models and test failure rates Genotype
and phenotype of the fetus Clinical
specificity pre-analytic errors
analytic errors
post-analytic errors
According to the analysis shown earlier
(Question 9), the analytic specificity is 97.9 percent. (i.e., a
mutation is falsely reported to be present, or the wrong mutation is
reported in about 2 to 3 per hundred tests).
This rate is derived from external proficiency testing and,
therefore, may not reflect the checks and balances routinely in place in
the clinical laboratory that are designed to identify and correct
analytic errors. Most of
the errors identified by proficiency testing consist of assigning an
incorrect mutation. Routine confirmatory procedures would likely identify and
correct many of these errors (Question 14).
When “wrong mutation” errors are taken into account properly,
analytic specificity is increased to 99.5 percent.
This analysis utilizes six years of proficiency testing data.
Only one false positive result has been reported from that source
for the last four years. Thus, an analytic false positive rate of 5 per 1000 cystic
fibrosis mutation analyses appears reasonable.
If this is true, how often will a positive couple be falsely
identified? A false
positive couple will occur most often in situations where one partner
actually has an identified mutation.
About 1 in every 28 non-Hispanic Caucasian individuals (1/25 *
0.88) will be correctly identified as being a carrier.
For every thousand such couples, five of the partners might be
expected to have a false positive test result.
Thus, a false positive couple is expected to occur in 5 of every
28,000 non-Hispanic Caucasian couples tested (1:5600), in comparison to
35 of every 28,000 non-Hispanic Caucasian couples who are truly positive
(1:800). Thus, without
confirmatory testing, perhaps as many as 1 in every 7 positive couples
might be incorrectly classified. How
many of these are likely to be correctly reclassified by confirmatory
testing? If all positive
couples were to provide another sample and that sample were to be
analyzed using a different methodology, perhaps all such errors would be
resolved. This may not be
done, however, in all screening laboratories.
If such confirmatory testing is not done, these false positive
couples are unlikely to be found as part of the routine diagnostic
testing of the fetus, since it is expected that 3 of every 4 fetuses of
true positive couples will not have two mutations present.
Some information about the possible
impact of confirmatory testing is available from the European external
proficiency testing program (Cuppens and Cassiman, 1995).
In that program, the protocol included a follow-up request to
laboratories with incorrect cystic fibrosis testing results.
They were asked to repeat the analysis. Under these unblinded
conditions, three laboratories
repeated the analysis of a false positive result and in all three
instances, the correct genotype was confirmed. Several other false positive results were not repeated and/or
not reported to the program. References Cuppens
H, Cassiman JJ. 1995. A quality
control study of CFTR mutation screening in 40 different European
laboratories. Eur
J Hum Genet 3:235-245. Giorgi
S, Tandoi C, Ciminelli BM, Modiano G.
1997. A correction
of the estimates of the least common cystic fibrosis (CF) mutations
published by “The Cystic Fibrosis Genetic Analysis Consortium” in
1994. Gene Geograph 11:57-59. Grody WW,
Desnick RJ. 2001.
Cystic fibrosis population carrier screening: Here at last –
Are we ready? Genet
Med 3:87-90. Heim R,
Sugarman EA, Allitto BA. 2001.
Improved detection of cystic fibrosis mutations in the
heterogeneous US population using an expanded, pan-ethnic mutation
panel. Genet Med 3:168-176. Kazazian
HH for the Cystic Fibrosis Genetic Analysis consortium.
1994. Population
variation of common cystic fibrosis mutations.
Hum Mutat 4:167-177. Palomaki GE,
Haddow JE, Bradley LA, FitzSimmons SC.
2002. An updated
assessment of cystic fibrosis mutation frequencies in non-Hispanic
Caucasians. Genet
Med, 4:90-94. Witt DR, Schaefer C, Hallam P, Wi S, Blumberg B, Fishbach A, Holtzman J, Kornfeld S, Lee R, Nemzer L, Palmer R. 1996. Cystic fibrosis heterozygote screening in 5,161 pregnant women. Am J Hum Genet 58:823-835. |
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Updated on August 13, 2004