diagnostic techniques

1. CLINICAL REVIEW David W. Eisele, MD, Section Editor
Adjunctive diagnostic techniques for oral lesions of unknown malignant potential:
Systematic review with meta-analysis
Colin Fuller, MD, MS,1*
Ryan Camilon, BA,1
Shaun Nguyen, MD, MA,1
Jon Jennings, MD,2
Terry Day, MD,1
M. Boyd Gillespie, MD, MSc,1
1
Department of Otolaryngology–Head and Neck Surgery, Medical University of South Carolina, Charleston, South Carolina, 2
Department of Emergency Medicine, Medical University
of South Carolina, Charleston, South Carolina.
Accepted 1 March 2014
Published online 5 May 2014 in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/hed.23667
ABSTRACT: Background. The purpose of this study was to critically
review the published evidence concerning adjunctive diagnostic techni-
ques in the diagnosis of oral lesions of unknown malignant potential.
Methods. We conducted a systematic literature review with meta-
analysis using PubMed to search for articles published from June
1993 through June 2013 to identify prospective studies evaluating
any diagnostic method, with tissue biopsy confirmation, in clinically
evident oral lesions of unknown malignant potential. Aggregate
weighted totals and SEs for true, false-positive, false-negative, and
inadequate results were calculated and compared among
subgroups.
Results. Forty-eight articles satisfying inclusion criteria were identified.
Twenty-five were included in quantitative synthesis.
Conclusion. Oral cytology holds higher diagnostic value than specialist’s
oral examination, which holds higher value than in vivo toluidine blue stain-
ing. This study does not support the use of computer-aided or liquid-based
cytology. Future studies should be designed to test multiple methods in the
same patient population to allow direct comparison among various techni-
ques. VC 2014 Wiley Periodicals, Inc. Head Neck 37: 755–762, 2015
KEY WORDS: oral cancer, oral lesion, oral premalignancy, oral
screening, oral cancer, early detection
INTRODUCTION
Oral cancer is the eighth most common cancer world-
wide.1
In the United States alone, there were an estimated
27,450 new cases of oral cancer in 2013, and it caused an
estimated 5,490 deaths.2
Although not among the most
common cancers in the United States, oral cancer is asso-
ciated with a high degree of morbidity and mortality,
which varies widely with staging. It has been demon-
strated that early detection is crucial to optimal outcomes.
As of 2009, pooled five-year relative survival for stage
III and IV disease for oral and oropharyngeal cancer was
estimated at 59.2%, whereas that of stage I and II disease
was 82.7%.3
In certain parts of the world, oral cancer
incidence is much higher. In south-central Asia, cancer of
the oral cavity is among the three most common types of
cancer.1
Despite the need for earlier diagnosis of oral can-
cer, in the United States, only 33% of oral and oropharyn-
geal cancer was diagnosed at an early, “localized” stage
from 2006 to 2010.4
Because of the deadly nature of oral
cancer and the accessibility of the oral cavity for testing,
early detection is an active field of research.
Diagnosis of oral cancer begins with a thorough history,
followed by conventional oral examination (COE). When
a suspicious lesion is identified, a full-thickness tissue
biopsy, such as punch biopsy, incisional biopsy, or exci-
sional biopsy, is often performed as the “gold standard”
test for diagnosing oral cancer. However, these tests are
not without limitations. Biopsy usually requires a special-
ist and access to a pathologist familiar with oral cancer.
Many techniques have been advocated over the past sev-
eral decades as aids or adjuncts in identifying which
lesions are suspicious enough to require biopsy. Unfortu-
nately, there remains some confusion and controversy in
the literature about which, if any, of these “adjunctive
techniques” are most reliable.
In a 2008 review, Lingen et al5
made the important dis-
tinction between the “screening” and “case-finding” steps
in mucosal diagnostics. Screening is defined as an attempt
to detect unknown lesions, whereas case-finding is an
attempt to diagnose known lesions. This study is
restricted to determining the utility of case-finding techni-
ques for oral cancer and dysplasia.
Case-finding techniques may have great benefit to pri-
mary care providers who must determine which patients
need referral to a specialist for definitive biopsy. This
systematic review and meta-analysis aims to elucidate the
utility and accuracy of adjunctive diagnostic techniques
for oral potentially malignant lesions.
This article was published online on 5 May 2014. The affiliations were
incorrect. This notice is included in the online and print versions to indicate
that both have been corrected 22 May 2014.
*Corresponding author: C. Fuller, Department of Otolaryngology–Head and
Neck Surgery, Medical University of South Carolina, MSC 550, 135 Rutledge
Ave, Charleston, SC 29403. E-mail: cwfull@gmail.com
Additional Supporting Information may be found in the online version of this
article.
HEAD & NECK—DOI 10.1002/HED MAY 2015 755

2. METHODS
Literature search
Inclusion criteria for this systematic review were devel-
oped in two phases. Before conducting a literature search,
the first set of inclusion criteria were agreed upon
(Table 1).
The literature search strategy can be found in the Pre-
ferred Reporting Items for Systematic reviews and Meta-
Analyses-compliant literature review diagram (Figure 1). A
PubMed search was performed by one author (C. F.) for
articles published between June 1993 and June 2013 using
the predetermined search terms (Appendix, online only;
Figure i). This search yielded a total of 2,488 references
when English-language and human subject constraints
were used. Eighty-eight additional articles were identified
by examining the reference lists of captured articles. A
Cochrane Library search (April 2008 to June 2013) was
also performed using the search term “oral neoplasm,”
which returned six references. References were screened
manually according to their titles and then based on
abstracts. 144 unique articles were identified that poten-
tially satisfied the first five inclusion criteria.
After assessing the volume of articles pending further
review, additional inclusion criteria were established,
which are listed in Table 1. Additional articles obtained
from reference lists that were older than June 1993 would
be included in the systematic review, but not the meta-
analysis.
Data extraction
Data from all articles included in the quantitative analy-
sis were abstracted by 2 authors independently (C. F. and
R. C.). Data were only collected if a 2 3 2 contingency
table (test result vs presence of disease according to
biopsy) could be constructed from the data presented.
These data were double-checked against any stated sum-
mary statistics in each article, such as sensitivity, specific-
ity, positive predictive value (PPV), negative predictive
value (NPV), and accuracy. In certain cases, the raw data
were reconstituted from these summary statistics by deter-
mining the whole number ratios that produced them. Data
reconstitution could be precisely achieved by solving five
equations for five unknown variables if sample size, sen-
sitivity, specificity, PPV, and NPV were reported (Appen-
dix, online only; Figure ii). When discrepancies arose, the
original article’s authors were contacted for comment if
the article had been published in the last ten years. Fail-
ing this, consensus was reached among all authors regard-
ing the validity of data inclusion.
Some inclusion criteria pertained to overall study
design, whereas others pertained to the characteristics of
the patients or their lesions (Table 1). When only some of
the patients satisfied these latter inclusion criteria, efforts
were made to extract only the data that described qualify-
ing lesions or patients. When this was not possible, con-
tact with the original authors was attempted if the article
was ten years old or less, and consensus was reached
among all authors.
When diagnostic test results were qualitative, we con-
sidered the presence of any level of concern for dysplasia
or cancer to be positive, including “atypical,”
“equivocal,” or any other result that implied the presence
of malignancy/premalignancy; results such as
“inflammation” or “hyperplasia” were considered nega-
tive, along with “benign” and “normal” results. Gold
standard results positive for cancer or any amount of dys-
plasia were also considered positive. In cases in which
articles used a different cutoff for defining positive and
negative test/biopsy results, contact with the original
authors was attempted if the article was ten years old or
less. If raw data could not be recovered, the authors’ defi-
nitions of positive and negative results were accepted.
This was only true of two of the included articles,6,7
both
of which reported the same study. This study defined the
cutoff between negative and positive to be between “oral
intraepithelial neoplasia I” and “oral intraepithelial neo-
plasia II.”
When test results were expressed quantitatively, the
authors’ cutoff for test results indicating dysplasia was
accepted as the cutoff for positivity, although the algo-
rithm used to generate the cutoff was noted. When multi-
ple algorithms were assessed, the dataset using the
algorithm with the highest accuracy was used to represent
the study in the analysis.
Where available, data on the results of COE were also
tabulated. Again, these data were only included when the
entire group of patients evaluated also underwent biopsy.
COE data was captured only when a benign versus not
benign lesion delineation was obvious. COE data was
excluded when the COE or visual impression declared an
area of mucosa to be “normal,” because this meta-analysis
evaluates the quality of adjuncts and COE in determining
the malignant potential of lesions, rather than normal
mucosa.
The cytology methods are prone to generating
“inadequate” or “unreadable” results. For these studies, an
additional analysis was performed to examine differences
in inadequacy rate between cytology methods. Only studies
that specifically reported the number of qualifying
TABLE 1. List of inclusion criteria.
First phase inclusion criteria
la. Oral cancer adjunct tested against gold standard tissue biopsy
2a. 10 or more patients studied
3a. English language publications only
4a. Published in peer-reviewed journal
5a. Adult population only
Second phase inclusion criteria
lb. Gold standard used for definitive diagnosis in all patients or in
all patients within a prospectively-determined subgroup
2b. Adjunct attempts to diagnose dysplasia, rather than simply
indicating a correlation
3b. Quantitative data presented that allows for the abstraction of
232 contingency table (disease vs. test result)
4b. If multiple tests evaluated, clinical characteristics could not be
used to determine which adjunct was used
5b. Adjunct used prospectively on lesions without histologically
confirmed diagnosis
6b. Patients have no history of cancer
7b. No history or anticancer treatment for the lesion in question
FULLER ET AL.
756 HEAD & NECK—DOI 10.1002/HED MAY 2015

3. inadequate samples would be included for this part of the
analysis.
Statistical analysis
Once all contingency tables for each included study
were constructed, true and false-positive, true and false-
negative, and inadequate results were summed for each
group of datasets. For sensitivity calculations, the total
with dysplasia or cancer according to gold standard was
considered the sample size, whereas the “proportion” was
each study’s sensitivity, to generate overall sensitivity and
95% confidence intervals (CIs). Similarly, for specificity
and accuracy, the sample size was the number of benign
lesions or total lesions (minus inadequate results), respec-
tively, in each dataset, whereas the specificity or accu-
racy, respectively, was the “proportion.”
A meta-analysis of proportions was then conducted on
the sensitivity, specificity, and accuracy of each group and
subgroup, using MedCalc 12.7.0 (MedCalc Software bvba,
Belgium). Analysis of pooled proportions was performed
where appropriate. MedCalc used a Freeman–Tukey trans-
formation8
(arcsine square root transformation) to calculate
the weighted summary proportion under the fixed and
FIGURE 1. Preferred Reporting Items for
Systematic Reviews and Meta-Analyses
literature search flow diagram from origi-
nal search through eventual inclusion of
qualifying data.
FIGURE 2. Conventional oral
examination results. Forest plot
for sensitivity, specificity, and
accuracy of conventional oral
examination datasets. For
explanation of random versus
fixed effects models, see
“Statistical Analysis” subsection
in Methods section. [Color fig-
ure can be viewed in the online
issue, which is available at
wileyonlinelibrary.com.]
DIAGNOSTIC TECHNIQUES FOR ORAL LESIONS OF UNKNOWN MALIGNANT POTENTIAL
HEAD & NECK—DOI 10.1002/HED MAY 2015 757

4. random effects models.9
Data were presented as weighted
proportions with corresponding 95% CIs. Both the fixed
effects model and the random effects model were used in
this study. Under the fixed effects model, it is assumed that
all studies come from a common population, and that the
effect size (the proportion) is not significantly different
among the different trials. This assumption is tested by the
“heterogeneity test” or I2
statistic. If this test yields a low
p value < .05, then the fixed effects model may be invalid.
In this case, the random effects model may be more appro-
priate, in which both the random variation within the stud-
ies and the variation between the different studies is
incorporated.
In addition, a chi-square test with Yates’ correction for
continuity was applied with two-sided (or two-tailed) p
values for the comparison of two proportions from inde-
pendent samples expressed as a percentage, as calculated
from the aforementioned aggregations. For each aggrega-
tion, the random effects result was used when the I2
test
for heterogeneity yielded a p value < .05; otherwise, the
fixed effects result was used. Each group was weighted
according to the number of patients with dysplastic/malig-
nant lesions, benign lesions, or total lesions with adequate
results, respectively. When the calculated p value was
<.05, the conclusion was that the two proportions were
significantly different.
RESULTS
A total of 48 articles were identified as eligible for
qualitative analysis,6,7,10–56
37 of which were “modern
era” articles and, thus, eligible for inclusion in the aggre-
gated quantitative analysis.6,7,10–32,45–56
One pair of
articles6,7
reported data from the same study, but, in this
case, the “duplicate” aided in the reconstitution of raw
data. The 37 modern articles reported 43 inclusion
criteria-satisfying datasets because many studies evaluated
multiple techniques, including all studies that reported
qualifying results of COE.
Data were included in the quantitative analysis and
aggregated for comparison for any techniques that had at
least three includable datasets. This left 25 articles across
five different adjuncts.6,7,10–32
These techniques were COE
(three datasets), cytology (12 datasets), toluidine blue vital
staining (eight datasets), laser-induced autofluorescence
(LIAF) spectroscopy (four datasets) and diffuse reflectance
spectroscopy (DRS; three datasets). A total of 2,184 quali-
fying measurements were conducted in these studies on a
TABLE 3. Overall technique comparisons.
Sensitivity
Technique D1C Sen TB COE Cytology LIAF
DRS 101 98.6 vs <0.001 0.014 0.007 0.990
LIAF 117 97.7 vs <0.001 0.026 0.010 -
Cytology 477 89.7 vs 0.006 0.965 - -
COE 69 88.7 vs 0.263 - - -
TB 240 82.1 vs - - - -
Specificity
Technique Ben Spe TB COE DRS LIAF
Cytology 670 89.8 vs <0.001 <0.001 0.540 0.626
LIAF 23 84.4 vs 0.006 0.064 0.763 -
DRS 21 83.2 vs 0.013 0.098 - -
COE 80 60.9 vs 0.235 - - -
TB 349 52.8 vs - - - -
Accuracy
Technique N Acc TB COE Cytology LIAF
DRS 122 96.5 vs <0.001 <0.001 0.001 0.944
LIAF 140 95.9 vs <0.001 <0.001 0.001 -
Cytology 1147 85.7 vs <0.001 0.014 - -
COE 149 77.6 vs 0.014 - - -
TB 589 66.7 - - - - -
Abbreviations: D1C, number of dysplasias and cancers by gold standard; Sen, sensitivity; COE, conventional oral exam; TB, toluidine blue; LIAF, laser-induced autofluorescence; DRS, diffuse reflec-
tance spectroscopy; Ben, number of benign lesions by gold standard; N, overall sample size (minus inadequate test results); Acc, accuracy).
Overall comparisons proportion using calculated values of sensitivity, specificity and accuracy from fixed or random effects models (see Appendix) and number of dysplastic/cancerous, benign and
total lesions, respectively. Techniques are ordered in descending quality. Statistically significant values are bolded and italicized, favoring the technique in the left-hand column.
TABLE 2. Diagnostic methods analyzed.
Conventional Oral Examination—examination conducted under normal, clinical fluorescent white lighting, without the use of stains, light filters or
magnification
Oral Cytology—the microscopic examination of superficial oral tissue harvested by non-invasive means (including brush, spatula, curette, etc.)
Toluidine Blue Staining—the use of toluidine blue (i.e. tolonium chloride) dye to stain lesions in vivo, under conventional, white fluorescent lighting
Laser-induced Autofluorescence Spectroscopy—the use of specific excitation wavelengths to illicit detectable fluorescence spectra in native oral
lesions, without the use of “photosensitizers” such as 5-aminolevulinic acid, by any excitation wavelength or spectroscopic analysis algorithm
Diffuse Reflectance Spectroscopy—the use of photodetection to analyze the diffuse reflectance spectra of oral lesions, by any spectroscopic anal-
ysis algorithm
FULLER ET AL.
758 HEAD NECK—DOI 10.1002/HED MAY 2015

5. total of 1,887 unique qualifying lesions. Appendix Tables i
to v, online only, summarize these studies. A brief explana-
tion of each of the techniques evaluated by articles included
in our quantitative synthesis can be found in Table 2. Fur-
ther basic science discussions of these techniques are
included in Appendix section A, online only.
The remaining 24 articles analyzed the value of many
additional techniques, or were published before 1993 and,
thus, not considered “modern era.” However, the findings
from these articles, including sensitivity, specificity, and
accuracy are summarized in Appendix Table vi, online only.
Direct comparisons between each of the 5 techniques
are found in Table 3. A set of sample Forest plots for
COE is found in Figure 2. The remaining Forest plots are
presented in Appendix Figures iii to vi, online only. A
more detailed discussion of the results of the meta-
analysis can be found in Appendix section C, online only.
The most sensitive technique was DRS (98.6%), fol-
lowed closely by LIAF (97.7%; Table 3). These techni-
ques each demonstrated significantly better sensitivity
than the remaining three techniques (COE, cytology, and
toluidine blue staining). The least sensitive technique was
toluidine blue (82.1%), which was significantly worse
than DRS, LIAF, and cytology.
The most specific technique was cytology (89.8%),
whereas the least specific technique was toluidine blue
(52.8%). Toluidine blue was less specific than any other
technique except COE.
The most accurate tests were DRS and LIAF (96.5%
and 95.9%, respectively). They were each more accurate
than any of the remaining three techniques. Toluidine
blue was the least accurate test (66.7%) and was signifi-
cantly outperformed in this category by the four other
tests. Within each technique category, subgroups were
established to investigate comparisons between variations
in technique (Table 4).
The single cytology dataset presenting results for
wooden spatula harvesting demonstrated significantly
higher specificity and accuracy compared to brush biopsy.
Conventionally read brush biopsy outperformed
computer-assisted brush biopsy based on specificity only.
The older, corporate-sponsored OralCDx trial demon-
strated significantly higher sensitivity, specificity, and
accuracy than the two newer OralCDx datasets collec-
tively. No other subgroup comparisons demonstrated stat-
istically significant differences.
DISCUSSION
In discussing the implications of this analysis, the authors
first wish to address its limitations. The most important
limitation of this meta-analysis is the variability in the
patient population between studies. This is not only impor-
tant with regard to patient demographics, but also the
lesions they present. Lesions that seem to be frankly can-
cerous should be referred immediately to a surgeon and
biopsied or excised, whereas lesions that have obviously
nonmalignant etiologies instead warrant observation and
close follow-up; diagnostic adjuncts are most valuable in
assessing the lesions that fall in the wide gap between these
two categories, and the less experienced the examiner, gen-
erally the wider the gap. Although the inclusion criteria
were intended to limit data only to lesions that had not
been definitively diagnosed by biopsy, this still leaves a
TABLE 4. Subgroup comparisons.
Technique p-value Technique
Wooden spatula cytology (A) vs. Brush cytology (B)
Sen, D1C 77.8%, 9 0.489 90.4%, 468
Spe, Ben 100%, 71 0.004 88.0%, 599
Acc, N 97.5%, 80 0.003 84.4%, 1067
OralCDx (C) vs. Conventional brush cytology (D)
Sen, D1C 94.3%, 160 0.067 88.6%, 308
Spe, Ben 83.4, 286 0.026 89.9%, 313
Acc, N 84.9%, 446 0.859 84.1%, 621
Sciubba (OralCDx) (E) vs. Recent OralCDx (F)
Sen, D1C 100%, 102 0.001 87.8%, 58
Spe, Ben 92.9%, 196 0.001 76.8%, 90
Acc, N 95.3%, 298 0.001 77.6%, 148
Toluidine blue application (G) vs. Toluidine blue rinse (H)
Sen, D1C 84.8%, 171 0.109 75%, 69
Spe, Ben 53.9%, 53.9 0.611 50.6%, 181
Acc, N 69.0%, 339 0.226 63.9%, 250
Toluidine blue Mashberg (I) vs. Toluidine blue non-Mashberg (J)
Sen, D1C 82.9%, 26 0.935 81.4%, 214
Spe, Ben 54.5%, 67 0.816 52.0%, 282
Acc, N 63.2%, 93 0.444 67.9%, 496
LIAF (dorsal/ventral tongue) (K) vs. LIAF (other locations) (L)
Sen, D1C 98.3%, 26 0.643 97.2%, 57
Spe, Ben 50.0%, 2 0.706 87.7%, 20
Acc, N 94.3%, 28 0.870 96.1%, 64
Abbreviations: Sen, sensitivity; D1C, number of dysplasias and cancers by gold standard; Spe, specificity; Ben, number of benign lesions by gold standard; Acc, Accuracy; N, sample size; LIAF,
laser-induced autofluorescence).
Direct comparison of proportions between dataset subgroups, using the overall sensitivity, specificity and accuracy calculated from fixed or random effects models (see figures). P-values indicating
significant differences are listed in bold print, with the better technique also listed in bold print. (Studies composing these subgroups are listed in Appendix Tables i-v).
DIAGNOSTIC TECHNIQUES FOR ORAL LESIONS OF UNKNOWN MALIGNANT POTENTIAL
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6. vast range of clinical possibilities, for some of whom a
diagnostic adjunct may be inappropriate.
Because it is very likely that the research studies were
conducted more often by specialists with an interest in
oral cavity cancer than by general clinicians, the exam-
iners that determined subject inclusion were also likely to
have excellent clinical judgment in determining poten-
tially dysplastic lesions. This may limit the applicability
of this data to general medical settings.
Early detection of oral cancer is rightfully an important
focus of research. The impact of earlier diagnosis for all
cancers is obvious, but is of particular value with regard to
the oral cavity because of reduced survival and quality of
life that occurs with later diagnosis. This persists despite
the accessibility of the oral cavity to direct examination.
Yet there still remains considerable debate as to the clinical
value of various oral cancer diagnostic adjuncts for clini-
cians at various levels of specialization. There are two
main clinical questions at issue; (1) What resources should
a general dentist or general medical practitioner bring to
bear when confronted by a lesion of uncertain malignant
potential; and (2) What resources are valuable for a cancer
specialist who may have the same question?
The former question is critical from a broad epidemio-
logic standpoint, especially in the third world or even
among rural general clinicians in developed nations. The
ideal test for the general practitioner would be one that is
inexpensive, noninvasive, sensitive, and expedient. How-
ever, even the judgment of specialists may be aided by
the use of these adjunctive tools, because the higher vol-
ume of potentially malignant lesions in their practice
would allow an adjunct to potentially save a larger num-
ber of patients from unnecessary biopsy.
The merits and drawbacks of each of the included tech-
niques are discussed below, considering the data pre-
sented in the meta-analysis.
Conventional oral examination
To the authors’ knowledge, this is the first meta-
analysis evaluating prospective clinical oral examinations
made by experts in oral cancer against the gold standard
of tissue biopsy.
One limitation of the COE data specifically is the
observer effect (or so-called “Hawthorn effect”) upon the
clinical examination. However, in addition to the behav-
ioral changes that occurred simply because of the knowl-
edge that one is being observed, there may have been some
semiconscious change to the evaluation. Because the eval-
uator knew that all of the lesions would receive a biopsy
anyway, the risk of a missed cancer diagnosis because of
an examiner’s error was completely ameliorated by each
patients’ inclusion in the prospective studies. There is a
chance that this changed the subjective cutoff for each
assessment to one that may not be used by that evaluator
clinically.
Cytology and noninvasive tissue sampling
Based on the meta-analytic data alone, it seems that
noninvasive cytology is quite useful. We demonstrate a
statistically significantly improved specificity and accu-
racy of cytology over a COE by a cancer specialist.
Despite this diagnostic improvement, in rural or under-
served areas, the use of this technique could delay more
definitive diagnosis by a week or more while the speci-
men is in transit and in process. Furthermore, of the two
main clinically available adjuncts analyzed here (the other
being vital staining), cytology is considerably more
expensive. Out-of-pocket cost charged by CDx Diagnos-
tics for OralCDx sample analysis is $225. According to
the authors’ institution chargemaster, the out-of-pocket
cost for conventionally read oral smear cytology is $186,
whereas the out-of-pocket cost for conventionally read
liquid-based cytology is $300. Meanwhile, a 100-mL bot-
tle of 1% toluidine blue can be purchased at retail for
about $15.
This study demonstrated a significantly better specific-
ity by conventional cytology compared to the proprietary
computer-based OralCDx system. The data also demon-
strate significant differences in the sensitivity, specificity,
and accuracy of the initial corporate-sponsored trial14
and
the pooled sensitivity of older trials (Table 4).20,21
Clinicians must interpret the preceding data with cau-
tion. An important limitation of the comparison between
OralCDx and conventional cytology is the nature of the
inclusion criteria. Disease progression affects sensitivity
and specificity (typically later-stage disease is easier to
diagnose) even if prevalence does not. The two more
recent Oral CDx articles specifically excluded any
patients who were diagnosed on examination with frankly
cancerous lesions, and one of them also excluded clini-
cally diagnosed dysplasias. This likely contributed to the
statistically significant difference in sensitivity between
this dataset and the dataset published by Sciubba et al,14
in which biopsies were performed only on patients pro-
spectively determined likely to have cancer. This under-
lines the limitation stated above regarding population
heterogeneity. In addition, spatula sampling of oral
lesions was demonstrated valuable by this meta-analysis.
Only one article evaluated non-Papanicolaou/hematoxy-
lin-eosin staining methods,22
and only one article evaluated
liquid-based cytology.19
The small sets of data presented
by these studies (N 5 20 and 26, respectively) were not of
sufficient statistical power to demonstrate statistical signifi-
cance, even if such a difference exists (data not shown).
We consider acridine orange staining and liquid-based
cytology to offer promise as a future research topic, but this
meta-analysis does not support their routine use. This meta-
analysis could not demonstrate any statistically significant
difference in inadequacy rate among cytology methods.
Vital staining techniques
Despite its affordability, according to this analysis and
review, toluidine blue staining does not improve on an
oral examination by a cancer specialist once a lesion has
been identified. In fact, its use seems to obscure the
examination results because the COE accuracy was signif-
icantly better than the accuracy of toluidine blue. Tolui-
dine blue was also outperformed based on accuracy by
every other technique in the quantitative synthesis.
However, this does not mean that the stain has no value
at all. The value of the dye as an oral cancer screening
tool was not evaluated in this study. There were also no
data on the accuracy of a clinical examination performed
FULLER ET AL.
760 HEAD NECK—DOI 10.1002/HED MAY 2015

7. by a general medical or dental practitioner, and there may
be a use for the dye in the hands of a generalist. How-
ever, the staining pattern in each of the studies was also
likely interpreted by an expert in oral cancer rather than a
generalist who may also be a poorer judge of staining
results.
Laser-induced autofluorescence and diffuse reflectance
spectroscopy
This meta-analysis identified a total of five studies
using the LIAF and/or DRS. Four of these studies shared
one author, and three of them had the same primary
author. The homogeneity of authorship for these techni-
ques severely limits the generalizability of the meta-
analytic data. The primary author for three of these stud-
ies29,30,32
confirmed the lack of patient overlap between
studies evaluating the same adjunct.
Perhaps the biggest caveat for interpreting the spectro-
scopic data is the retrospective nature of model construc-
tion inherent to the development of any new diagnostic
test. Only a single study29
validated their constructed
model prospectively on a second set of undiagnosed
lesions. We strongly encourage future researchers to adopt
this method of model validation, as it is the best way to
demonstrate the applicability of the adjunct to actual
patients.
Nonetheless, the data from these techniques were impres-
sive. By sensitivity and overall accuracy, they outper-
formed all other techniques here presented (Table 3).
Accuracy data should also be interpreted with caution. The
apparent accuracy of a test (defined as “true results/total
results”) can be affected by the prevalence of disease, espe-
cially when a test’s sensitivity and specificity are appreci-
ably different from one another. For example, a highly
sensitive but poorly specific test would look more accurate
when used on a patient population with high prevalence of
disease. This would have a greater effect on the accuracy
of the spectroscopic studies, because their prevalence of
disease was very high, and these techniques seem to be
more sensitive than they are specific.
Before declaring that these techniques are the “wave of
the future” for oral cancer diagnosis, further study verify-
ing these models prospectively is needed. However, the
success of the spectroscopic diagnostic strategies is
encouraging compared to the remaining three methods.
Spectroscopy has the potential to offer a noninvasive
instantaneous answer to the clinical question of whether a
lesion is benign, dysplastic, or cancerous. The question of
whether these can be successfully brought to bear in a
clinical setting may rest on the system’s financial accessi-
bility to the clinicians that would benefit most from using
them: rural and general clinician.
It is commonly noted that LIAF has limited use in lesions
of the lateral and dorsal tongue and vermillion border of
the lip because normal mucosa in these areas generates a
fluorescence spectrum analogous to that of cancer.
Although this was demonstrated in one of the included
articles,30
the diagnostic errors were almost completely
confined to normal, lesion-free mucosa. We note that
because these spectroscopic techniques are under develop-
ment for use in evaluating known lesions, rather than scan-
ning to screen for unknown lesions, this drawback may not
significantly impact its clinical value. This analysis shows
no significant difference between the diagnostic accuracy
of LIAF for lesions in the dorsal and lateral tongue and its
accuracy for lesions elsewhere.
Avenues for future research
Considering the lower incidence rate of oral cancer
compared to other forms of malignancy, further study in
the area of known lesion diagnostics may hold the key to
reducing the mortality of this disease. Future research
should facilitate the evaluation of diagnostic adjuncts
against one another in the same patient population, with
confirmation in all patients by tissue biopsy. In addition,
the reporting of CIs or SEs alongside descriptive statis-
tics, such as sensitivity, specificity, PPV, NPV, accuracy,
and inadequacy rate is strongly encouraged. Without these
measures of confidence, comparisons between diagnostic
modalities hold far less value.
Future meta-analyses on this topic may continue to prove
quite valuable, as the sample sizes required to achieve sta-
tistical significance may outstrip the resources of any one
researcher or research group. Publication of raw data or its
inclusion in appendices for meta-analytic purposes is
important.
Researchers need to consider the examination skills of
the clinicians that are most likely to benefit from these
adjuncts. To evaluate whether any of these adjuncts are
useful to general dentists and medical doctors, the baseline
general practitioner COE must be studied against gold
standard biopsy. Future research methods should consider
defining their examination-based inclusion criteria by the
generalist’s examination, if these clinicians are the ones
who will most benefit from the use of the adjunct.
CONCLUSION
This meta-analysis demonstrates a statistically significant
improvement in diagnostic quality of oral cytology meth-
ods over COE based on superior specificity and overall
accuracy. This analysis does not support the use of more
costly versions of oral cytology, such as OralCDx
computer-assisted cytology or liquid-based cytology based
on diagnostic accuracy or inadequacy of the sample. Other
sampling techniques for cytology may hold promise, but
further study is needed to assess their diagnostic value. For
visible lesions, toluidine blue seems to hold little value.
Few head-to-head trials have been published evaluating dif-
ferent techniques in the same population.
Both LIAF and DRS had a significantly higher accuracy
than COE and toluidine blue staining, and significantly bet-
ter sensitivity than toluidine blue staining. DRS also dem-
onstrated significant improvement in sensitivity compared
to cytology. These diagnostic adjuncts are promising and
we encourage further research prospectively evaluating
these methods using established diagnostic algorithms.
Acknowledgments
The authors thank Drs. Hohlweg–Majert,18
Kaczmarzyk
and Mojsa,31
Narayanan and Mallia,29,30,32
and Joseph
Califano and David Sirois for their assistance with inter-
preting and clarifying data.
DIAGNOSTIC TECHNIQUES FOR ORAL LESIONS OF UNKNOWN MALIGNANT POTENTIAL
HEAD NECK—DOI 10.1002/HED MAY 2015 761

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