Journal of Cancer Therapy, 2012, 3, 662-672
http://dx.doi.org/10.4236/jct.2012.325086 Published Online October 2012 (http://www.SciRP.org/journal/jct)
1
Meta-Analysis: 18F-FDG PET or PET/CT for the
Evaluation of Neoadj uvant Chemotherapy in Locally
Advanced Breast Cancer
Yun Xi, Min Zhang, Rui Guo, Miao Zhang, Jiajia Hu, Biao Li*
Department of Nuclear Medicine, Ruijin Hospital, Shanghai, China.
Received April 22nd, 2012; revised May 26th, 2012; accepted June 15th, 2012
ABSTRACT
Purpose: To evaluate the accuracy and the predictive value of 18F-FDG PET or PET/CT in the assessment of neoadju-
vant chemotherapy (NAC) in locally advanced breast cancer by meta-analysis. Materials and Methods: Relevant
studies were identified by systematic searches of PUBMED and COCHRANE databases, published in English. To en-
sure homogeneity of all included studies, selection criteria were established and all the studies were scored according to
Quality Assessment of Diagnostic Accuracy Studies (QUADAS) criteria. Meta-analysis was done on the diagnostic
performance data from eligible studies. Draw funnel plots to explore the publication bias. Draw forest plots to exclude
abnormal data(s). Use Spearman correlation coefficients ρ, likelihood ratio χ2 test and I2 index in order to indicate het-
erogeneity. Estimate and compare the weighted summary sensitivities (SEs), specificities (SPs), diagnostic odds ratios
(DORs), and summary receiver operating characteristic (SROC) curves of PET and other examinations (measuring the
size of tumor). Subgroup analyses were performed to identify heterogeneity potential sources. Do Z test to find signifi-
cant difference between each results. Results: 27 groups of data in 19 eligible studies were included with a total of 1164
subjects evaluated by 18F-FDG PET or PET/CT and 291 ones evaluated by other examinations. Funnel plots showed the
existence of publication bias. Spearman correlation coefficients ρ, likelihood ratio χ2 test and I2 index explored the het-
erogeneity. The Results of the Weighted Summary: SEPET was significantly higher than SED [83.7% (329/393) vs.
59.0% (98/166), p < 0.001], SPPET was significantly higher than SPD [66.8% (512/766) vs. 40.8% (51/125), p < 0.001],
DORPET was significantly higher than DORD (14.02 vs. 1.29, p < 0.05). The results show that FDG-PET was more ac-
curate in assessment NAC efficiency. Draw SROC curves with Metadisc 14.0 and caculate results showed AUCPET and
Q*
PET were both significantly higher than AUCD and Q* D (AUCs 0.8838 vs. 0.6046; Q*s 0.8143 vs. 0.5788, p < 0.001),
which confirmed the advantage of FDG-PET. Subgroup analysis showed that performing FDG-PET after the 1st or 2nd
cycle of NAC was a litter better than later with higher SE (p = 0.083). Standardized uptake value (SUV) reduction rate
between 40% and 45% as FDG-PET response threshold value was used for its highest SP (p = 0.01), while no signifi-
cant difference was found comparing SEs and DORs (p > 0.05). Trend of higher SE and lower SP were found at ER
negative breast cancers than ER positive ones (SEs 93.94% vs. 83.33%; SPs 35.76% vs. 62.24%), though Z test did not
find significant difference (p > 0.05). Conclusion: This meta-analysis showed that FDG-PET or PET/CT does have a
higher global accuracy in assessing the response for NAC in breast cancer. Comparing with clinical response, metabolic
response plays a potential role in directing therapy for breast cancer. Factors which affected the accuracy of FDG-PET
assessmnet included PET timing point, SUV reduction rate as threshold value and ER expression.
Keywords: Breast Cancer; Fluorodeoxyglucose; Position Emission Tomography; Neoadjuvant Chemotherapy;
Meta-Analysis
1. Introduction
Breast carcinoma is the most common cancer in women
in Western Europe and the United States with an inci-
dence highest in the 40 - 55 age range, and its prevalence
is still on the rise [1,2]. It accounts for 40,000 and 14,000
deaths yearly in the US and UK, respectively, and that
makes it the second cause of cancer death in women in
those countries [1,3].
Neoadjuvant chemotherapy (NAC), initially used only
for locally advanced breast cancer, is now commonly
used in patients with operable but large breast cancer.
This strategy allows patients to undergo breast-conserv-
*Corresponding author.

Meta-Analysis: 18 F-FDG PET or PET/CT for the Evaluation of Neoadjuvant Chemotherapy in Locally
Advanced Breast Cancer
663
ing surgery and gives information on the efficacy of
chemotherapy [4]. Long-term outcomes are significantly
correlated with pathological tumour response rates [5].
Patients who achieve pathological complete response
(pCR) have longer disease-free and overall survival rates
compared with nonresponder [5-7]. Therefore an inva-
sive method for early evaluation of the response to NAC
in patients with operable breast cancer is necessary.
According to the recommendations of the American
Society of Clinical Oncology (ASCO) 2006 update of the
breast cancer follow-up and management guidelines in
the adjuvant setting, physical examination and mam-
mography should be used routinely in the breast cancer
surveillance. Additional imaging methods, such as ultra-
sound (US), computed tomography (CT) scans, breast
magnetic resonance imaging (MRI) and positron emis-
sion tomography (PET) with 18F-fluoro-deoxy-glucose
(FDG) scans are not recommended [8]. But physical
examination and mammography have their limitations,
especially for evaluation of the changes in breast tissue.
US, CT and MRI mainly provide information about the
tumor size to assess the response to NAC, which is called
clinical response. The whole-body imaging modality
PET provides information about the metabolical activity
of tumors to assess the response to NAC, which is called
metabolical response. Previous studies [9-13] performed
some meta-analysis to assess FDG-PET for the evalua-
tion of breast cancer recurrences and metastases. Thus,
Our study aims to perform a comprehensive systematic
review to obtain the role of an early evaluation with
FDG-PET of the response to NAC before surgery, and
we also focus on the comparison between clinical re-
sponse and metabolic response, which, to our knowledge,
had not previously been studied.
2. Materials and Methods
2.1. Data Sources and Eligibility
Published studies of NAC evaluation in breast cancer
with FDG-PET or PET/CT were identified by systematic
searches of PUBMED and COCHRANE databases. The
following kewords were used: (“PET” OR “positron
emission tomography” OR “FDG” OR “fluorodeoxyglu-
cose”) AND (“breast carcinoma” OR “breast cancer” OR
“carcinoma of breast”) AND (“neoadjuvant” OR “che-
motherapy”). Articles were limited to the period between
1966 and 2012, and were performed with the assistance
of JIAO TONG UNIVERSITY LIBRARIAN.
The inclusion criteria were as follows: 1) full reports
published in English; 2) articles dealt with the perform-
ance of PET (alone or in combination, but not in se-
quence); 3) use of 18F-FDG as imaging radiotracer; 4)
pathological results as golden standard; 5) changes of
semi-quantitative value were for evaluation criterion and
set a threshold value to distinguish between metabolical
responders and metabolical non-responders; 6) only arti-
cles that present sufficient data to calculate the true posi-
tive (TP), false positive (FP), false negative (FN), true
negative (TN) values were included; 7) sample size was
at least 10 subjects; 8) assess pre-chemotherapy and post-
chemotherapy in locally advanced breast cancers.
Since the validity of the individual studies may affect
the interpretation of a diagnostic meta-analysis, Quality
Assessment of Diagnostic Accuracy Studies (QUADAS)
criteria [14] were adapted for assessment the quality of
each article. Removing unsuitable items (question 3, 7, 9
were not suitable for our golden index standard—patho-
logical test; question 12 was not suitable for reference
test which set a threshold value for evaluation), there
remained ten (all items were listed in Table 1). Each
question should be answered as yes, no or unclear. All in-
cluded studies were scored on all 10 items to provide an
overall score. For the purpose of this analysis, “yes” was
scored as “1”, while “no” and “unclear” were both scored as
“0”. Articles with score upon “6” were eligible for analysis.
Six reviewers, among who 3 had at least 3 years work
experience in nuclear medicine, independently checked
retrieved articles. In case of discordances, a consensus
re-review between all reviewers was performed.
2.2. Data Synthesis and Statistical Analysis
Data from individual studies were summarized in a 2 × 2
table classifying patients or lesions as TP, FN, FP and
TN. If an article included several assessment time points,
they were enrolled into study as different groups of data.
If an article included upon two threshold values of semi-
quantitative value decrease rate, select the highest accu-
rate data.
Test publication bias by drawing funnel plots. Forest
plots were to find abnormal data to exclude. Test the fol-
lowing items to find heterogeneity: threshold effects be-
tween studies using Spearman correlation coefficients ρ
(the cutoff effect was considered present in case of a ρ
value > 0.4); heterogeneity using the likelihood ratio χ2
test (if p < 0.05 was considered having apparent hetero-
geneity) and I2 index which is a measure of the percent-
age of total variation across studies due to heterogeneity
beyond chance and takes values between 0 and 100%. Its
values over 50% indicate heterogeneity. If all tests con-
firmed publication bias and heterogeneity, a random ef-
fect model was used for the primary meta-analysis to
obtain the weighted mean sensitivity (SE), specificity
(SP) and diagnostic odds ratio (DOR) with 95% confi-
dence intervals (CIs) of FDG-PET and other examina-
tions. Otherwise, a fixed effect model was used. DOR is
the best single global measure of diagnostic test per-

Meta-Analysis: 18 F-FDG PET or PET/CT for the Evaluation of Neoadjuvant Chemotherapy in Locally
Advanced Breast Cancer
664
formance that encompasses both SE and SP. Golden standard was not pathological results (n = 4); 6)
The changes of semi-quantitative value were not as evalu-
ation criteria (n = 16); 7) Data were insufficient for cal-
culating SE and SP (n = 9); 8) Sample size was under 10
(n = 5); 9) Studies not compared changes of values be-
tween pre-therapy and post-therapy (n = 19). All of the
19 studies scored upon 6 according to QUADAS criteria.
Table 1 pooled the results of the distribution of study
design characteristics and Figure 1 summarizes the
QUADAS criteria results of the 19 studies. The informa-
tions of all included studies and the main characteristics
of data for evaluation metabolical response and clinical
response were listed in Tables 2-4. Because other ex-
aminations assessed the effect of NAC by tumor size, we
defined them as “D” for subscript.
Asymmetric summary receiver operating characteristic
(SROC) curves were fitted using weighted regression or
inverse variance method (Moses’ model [15]), and their
area under the curve (AUC) and Q* index calculated. AUC
summarizes diagnostic performance as a single number,
while Q* index is the point where SE and SP are equal.
When statistical heterogeneity was identified, sub-
group analysis was performed to identify its potential
sources (e.g., different PET timing points, response crite-
ria and molecular phenotype of primary breast cancer). Z
test was employed to identify if significant difference
existed between subgroups.
Z test was employed to identify if significant differ-
ence existed between two modalities of examinations and
subgroups, including SE, SP, DOR, AUC and Q* index.
If p < 0.05 was considered as statistically significant.
All of the statistical analyses were undertaken using
RevMan 5.1, STATA 11.0 and Meta-Disc14.0.
3. Results
3.1. Literature Search and Study Design
Characteristics
The computerized search yielded 202 primary studies, of
which 106 were excluded after reading titles and ab-
stracts because of the relationship far from our purpose.
Among the left 96 articles, 19 met all of the criteria
[16-34]. The reasons for exclusion were as follows: 1)
Cannot obtain full articles (n = 4); 2) Articles were re-
views, case reports or other non-treatises (n = 14); 3) The
evaluation lesions were non-locally breast carcinomas (n
= 5); 4) Radiotracer was other than FDG (n = 1); 5)
The total proportion of quality score was 81.58%, which suggested high
quality.
Figure 1. Summarises the QUADAS criteria results of the
19 studies.
Table 1. Results of the distribution of study design characteristics in 19 studies.
Question about study design characteristic Yes No Unclear
1 Was the spectrum of patients representative of the patients who receive the test in practice? 8 9 2
2 Were selection criteria clearly described? 13 3 3
3 Is the reference standard likely to help to correctly classify the target condition? / / /
4 Is the time between performance of the reference standard and the index test short enough? 11 7 1
5 Did the whole sample or a random selection of the sample receive verification by using a reference standard? 19 0 0
6 Did patients undergo examination with the same reference standard regardless of the index test result? 18 0 1
7 Was the reference standard performed independently of the index test? / / /
8 Was the execution of the index test described in sufficient detail to permit replication of the test? 19 0 0
9 Was the execution of the reference standard described in sufficent detail to permit replication of the test? / / /
10 Were the index test results interpreted without knowledge of the reference standard results? 13 2 4
11 Were the reference standard results interpreted without knowledge of the index standard results? 18 0 1
12 Were the same clinical data available when test results were interpreted as would be available in practice / / /
13 Were uninterpretable and/or intermediate test results reported? 19 0 0
14 Were withdrawals from the study explained? 17 0 2
Data were the numbers of responses from the QUADAS tool. The numbers indicated how many articles were assigned a point of “Yes”, “No” or “Unclear”.
Removed catalogue 3, 7, 9 because of insuitableness for our golden index test—pathological test and catalogue 12 of insuitableness for reference test which set
a threshold value for evaluation.

Meta-Analysis: 18 F-FDG PET or PET/CT for the Evaluation of Neoadjuvant Chemotherapy in Locally
Advanced Breast Cancer
665
Table 2. Main characteristics of all include d studie s.
No Author
Publication
year Age (y) Pre-treatment size (cm) Stage NAC regimen Surgery time
1 Schelling M [16] 2000 41 - 60 3.5 - 12.0 II-III anthracycline-based/combination 3rd/4th cycle
2 Smith IC [17] 2000 unknown 1 - 8 II-III anthracycline-based >5th cycle
3 Kim SJ [18] 2004 27 - 68 1.5 - 7.5 II-III taxane-based/combination unknown
4 Rousseau C [19] 2006 32.8 - 75 1 - 10 II-III anthracycline-based/combination 6th cycle
5 Li D [20] 2007 34 - 65 2.1 - 9.5 II-IV anthracycline-based/combination 3rd cycle
6 Berriolo-Riedinger A
[21] 2007 48 ± 9 unknown II-III anthracycline-based/taxane-base d/ combination 4th/6th cycle
7 McDermott GM [22] 2007 51 ± 10 >3 II-III anthracycline-based 6th/8th cycle
8 Duch J [23] 2009 32 - 82 >3 II-III anthracycline-based 4th cycle
9 Kumar A [24] 2009 25 - 60 4.1 - 12 II-III anthracycline-based 6th cycle
10 Schwarz-Dose J [25] 2009 29 - 65 3 - 12 II-III anthracycline + taxane 4th/6th cycle
11 Choi JH [26] 2010 24.1 - 63.1>4 II-III anthracycline-based/combination 3rd ~ 8th
cycle
12 Jung SY [27] 2010 21 - 64 unknown II-III taxane-based 4th cycle
13 Ueda S [28] 2010 60 - 83 1.2 - 4.9 II-III letrozole 12th week
14 Schneider-Kolsky ME
[29] 2010 30 - 70 >2 II-III anthracycline-based+taxane 8th cycle
15 Martoni AA [30] 2010 31 - 72 unknown II-IV anthracycline-based/taxane-base
d 6th/8th cycle
16 Park JS [31] 2011 28 - 67 1.3 - 10 II-III taxane-based/combination 3th/6th cycle
17 Ueda S [32] 2011 55 ± 9.8 ≤2 II-IV anthracycline-based+taxane 8th cycle
18 Park SH [33] 2011 27 - 60 >2 II-III taxane-based/combination 3th/6th cycle
19 Keam B [34] 2011 29 - 69 2 - 11 II-III anthracycline/taxane 3th cycle
NAC: neoadjuvant chemotherapy.
3.2. Publication Bias, Heterogeneity and Cutoff
Effect
After extraction informations of 19 articles, there in-
cluded 27 groups of data for FDG-PET and 8 groups of
data for other examinations. To assess a possible publi-
cation bias, scatter plots were designed using the log-
DORs of individual data against their sample size. The
funnel plots of FDG-PET and other examinations were
given in Figure 2. In detail, figure of FDG-PET showed
nearly symmetry but one plot beyond 95% CIs. Figure of
other examinations showed marked asymmetry with
fewer studies above the horizontal line. There were 2
plots beyond 95%CIs. Analysing with the figures, we
thought a possible publication bias in both FDG-PET and
oher examinations. The forest plots of DORs (Figure 3)
showed an abnormal value comparing others (other ex-
aminations of study written by Park JS [31]). The proba-
bly reason was that the study add a criterion of the en-
hancement significancy on post-chemotherapy MRI scan.
Therefore, other examination data of this study was ex-
cluded. The heterogeneity test results were as follows:
There was no heterogeneity for FDG-PET except the test
of SP. There was heterogeneity for other examinations
except the test of DOR, which confirmed either by like-
lihood ratio χ2 test or I2 index (Table 5). There was no
conclusive evidence of a cutoff effect for FDG-PET to
Spearman correlation coefficients (p value = 0.269 < 0.4).
But a cut off effect was present for other examinations (p
value = 0.714 > 0.4). As stated previously, a random ef-
fect model was used for analysing FDG-PET and other
examinations.
3.3. Pooled SE, Pooled SP and Pooled DOR
27 eligible groups of date were included with a total of
1164 subjects evaluated by FDG-PET or PET/CT and
291 ones evaluated by other examinations. On the basis
of a random effect model for analysing FDG-PET and
other examinations, weighted summary SEs, SPs and

Meta-Analysis: 18 F-FDG PET or PET/CT for the Evaluation of Neoadjuvant Chemotherapy in Locally
Advanced Breast Cancer
666
Table 3. Characteristics of the include d data for evaluation metabolical response.
No Equipment for evaluate metabolic response Second examination time Criteria Threshold Number of patients/lesions
1 PET 1st cycle SUVmax 55% 16
1 PET 2nd cycle SUVmax 55% 22
2 PET 1st cycle DUR 20% 29
3 PET Unknown SUVp 88% 25
4 PET/CT 1st cycle SUVmax 40% 63
4 PET/CT 2nd cycle SUVmax 40% 63
4 PET/CT 3rd cycle SUVmax 45% 63
5 PET/CT 3rd cycle SUV T/N 20% 45
6 PET 2nd cycle SUVmax 60% 47
7 PET 1st cycle SUVmax 64% 24
7 PET 3rd/4th cycle SUVmax 64% 13
7 PET 6th/8th cycle SUVmax 64% 20
8 PET/CT 2nd cycle SUVmax 40% 50
9 PET/CT 2nd cycle SUVmax 50% 23
10 PET 1st cycle SUVmax 50% 69
10 PET 2nd cycle SUVmax 50% 64
11 PET 3rd - 8th cycle SUVp 50% 41
12 PET 4th cycle SUVp 35.50% 66
13 PET/CT 4th week SUVmax 40% 12
14 PET/CT 4th cycle SUVmax 75% 60
15 PET/CT 2nd cycle SUVmax 50% 34
15 PET/CT 4th cycle SUVmax 50% 34
15 PET/CT 6th/8th cycle SUVmax 50% 34
16 PET/CT 3rd/6th cycle SUVmax 50% 32
17 PET/CT 4th cycle SUVmax 72.10% 98
18 PET/CT 3rd/6th cycle SUVmax 63.90% 34
19 PET/CT 1st cycle SUVmax 50% 78
SUV: standardized uptake value; SUVp: peak standardized uptake value; SUVmax: maximum standardized uptake value; SUV T/N: standardized uptake value of
tumor tissue compared with normal tissue; DUR: dose uptake ratio.
Table 4. Characteristics of the included data for evaluation clinical response.
No Equipment for evaluate metabolic response 2nd examination time Size threshold Number of patients/lesions
1 Mammo, US, MRI 4th/3rd cycle 50% 32
2 Palpation 1st cycle 50% 31
3 Majority with CT Unknown 50% 50
4 US 6th cycle 60% 63
4 Mammo 6th cycle 60% 63
9 Vernier calliper, CT 2nd cycle 50% 23
11 MRI 3rd - 8th cycle 30% 29
16 MRI 3rd/6th cycle 30% 32
Mammo: mammography; US: ultrasond; CT: computed tomography; MRI: magnetic resonance imaging.

Meta-Analysis: 18 F-FDG PET or PET/CT for the Evaluation of Neoadjuvant Chemotherapy in Locally
Advanced Breast Cancer
667
Figure 2. Funnel plot with pseudo 95% confidence limits.
Figure 3. Forest plots of FDG-PET and other examinations.
DORs of both modalities were shown in Table 5. Pooled
SEs of PET and other examinations were 83.7% (329/
393) and 59.0% (98/166), respectively. High statistical
significant difference was found (p < 0.001). Pooled SPs
of PET and other examinations were 66.8% (512/766) and
40.8% (51/125), respectively. High statistical significant
difference was found (p < 0.001). Pooled DORs of PET
and other examinations were 14.02 and 1.29, respectively.
Statistical significant difference was found (p = 0.015 <
0.05).
3.4. SROC Curves, AUC and the Q* Index
Summary receiver operating characteristic analysis was
used to generally compare FDG-PET and other examina-
tions (Figure 4). The AUCs of FDG-PET and other ex-
aminations were 0.8838 ± 0.0190, 0.6046 ± 0.1003.
AUCPET was significantly higher than AUCD (p <
0.001). The Q* index of FDG-PET and other examina-
tions were 0.8143 ± 0.0194, 0.5788 ± 0.0764. Q*
PET was
significantly higher than Q*
D (p < 0.001).
3.5. Subgroup Analysis for Primary Breast
Cancer Response
The heterogeneity of SP in FDG-PET among the 27
groups of data rationalized several subgroup analyses to
identify its possible sources. It was noted that those stud-
ies employed different regimen of FDG-PET, including
the PET timing points and cutoff values of semi-quanti-
tative value as metabolical response criteria. Influence of
different molecular phenotypes to the accuracy of FDG-
PET evaluation was also analysed.
Table 5 Test for heterogeneity and threshold effect in the
meta-analysis.
SE SP DOR
FDG-PET
Pooled value 83.7%** 66.8%** 14.017*
95% CIs [78.6%, 86.3%] [63.3%, 70.1%] [9.713, 20.229]
χ230.62 155.78 29.10
Likelihood
ratio p0.243 0.000 0.243
I2% 15.1% 83.3% 15.1%
Other examination
Pooled value 59.0%** 40.8%** 1.288*
95%CIs [51.1%, 66.6%] [32.1%, 49.9%] [0.560, 2.965]
χ245.00 27.72 11.06
Likelihood
ratio p0.000 0.000 0.086
I2% 86.7% 78.4% 45.8%
SE: sensitivity; SP: specificity; DOR: diagnostic odds ratio; 95%CIs: 95%
confidential interval;* means statistical significant difference;**means high
statistical significant difference.

Meta-Analysis: 18 F-FDG PET or PET/CT for the Evaluation of Neoadjuvant Chemotherapy in Locally
Advanced Breast Cancer
668
Figure 4. SROC curves of FDG-PET and other examina-
tions.
3.5.1. Evaluation of PET Timing Points
One study [28] used letrozole for NAC that chemother-
apy cycle was not as unit to measure PET timing points.
And one study [18] didn’t discribe time of the second
FDG- PET after completion of NAC. The remaining 25
groups of data were divided into 2 subgroups: evaluation
FDG-PET after 1 - 2 cycles of NAC (subgroup A) and
after upon 3 cycles (subgroup B). Results were showed
in Figure 5. Pooled SEs of subgroup A and subgroup B
were 86.0% (175/218) and 93.3% (150/172), respectively.
Low statistical significant difference was found (p =
0.083). Pooled SPs of FDG-PET and other examinations
were 72.7% (252/366) and 62.1% (241/371), respectively.
There was no statistical significant difference (p = 0.232).
Pooled DORs of PET and other examinations were 32.67
and 24.19, respectively. There was no statistical signifi-
cant difference, too (p = 0.447).
3.5.2. Cuto ff Value as PET Response Criteria
Two studies [17,20] were excluded for not using SUVmax
or SUVp as FDG-PET response criteria. And groups that
using under 40% or upon 70% for threshold value were
too few to consolidate, which were also excluded. Then
22 groups of data were divided into subgroup I (cutoff
value 40% - 45%), subgroup II (cutoff value 50% - 55%)
and subgroup III (cutoff value 60% - 65%). Results were
showed in Figure 6. Z test was employed which explored
high significant difference between subgroup I and sub-
group II comparing SPs (p = 0.01).
3.5.3. Influence of Different Molecular Phenotypes
Of all 19 studies, 4 consisted correlation bewteen SU-
Vmax and estrogen receptor [ER] expression. Data were
showed in Table 6. At ER positive group, pathological
response rate and metabolical response rate were 12.39%
and 48.42%, respectively, at the same time reduction rate
of SUV (△SUV%) was 45.00%; Pooled metabolical
response accuracy, SE and SP were 83.33% and 62.24%,
respectively. At ER negative group, pathological response
rate and metabolical response rate were 49.05% and
80.26%, respectively, meanwhile △SUV% was 62.95%;
pooled metabolical response accuracy, SE and SP were
93.94% and 35.76%, respectively. No significant differ-
ence was found in all above-mentioned results (p > 0.05).
Figure 5. Evaluation sensitivity and specifity with FDG-
PET according to different PET timing.
Figure 6. Evaluation sensitivity and specifity with FDG-
PET according to different cutoff values of semi-quantita-
tive reduction rate as PET response criteria.

Meta-Analysis: 18 F-FDG PET or PET/CT for the Evaluation of Neoadjuvant Chemotherapy in Locally
Advanced Breast Cancer
669
Table 6. Characteristics of response according to ER pression.
ER+ ER−
No Examination
time PR rate (%) MR rate
(%) SE (%) SP (%) △SUV (%)PR rate (%)MR rate (%) SE (%) SP (%) △SUV (%)
13 4th week / / 33.33 100.00 / / / / / /
15 2nd cycle 15.00 60.00 100.00 47.06 60.00 30.77 100.00 100.00 5.56 77.90
16 3rd or 6th cycle 14.29 / 100.00 33.33 / 88.89 / 100.00 50.00 /
19 1st cycle 7.89 36.84 100.00 68.57 30.00 27.50 60.53 81.82 51.72 48.00
ER: estrogen receptor; PR: pathological response; MR: metabolical response; SE: senstivity; SP △ : specificity; SUV%: decrease rate of maximum standardized
uptake value.
4. Discussion
Preclinical models have demonstrated that the admini-
stration of chemotherapy prior to tumor removal is bio-
logically more favorable than postoperative administra-
tion [35]. Effective preoperative chemotherapy can re-
duce the size of the primary tumor, thus allowing breast-
conserving surgery and also provides a prognostic infor-
mation compared with primary tumor resection followed
by adjuvant chemotherapy in patients with a pCR [36].
The early identification of non-responders can also avoid
an unnecessary delay in instituting alternative therapy.
Conventional breast imaging procedures, including mam-
mography, US, and MRI have been used for measuring
tumor size to derive the response to therapy. However,
the clinical response does not necessarily reflect the
histopathologic response because of the limited accuracy
and reproducibility in determining tumor size and the
delay between initiation of therapy and tumor shrinkage
[26].
Currently, histopathologic analysis is necessary to ac-
curately assess the response to NAC. PET imaging has
been proposed to improve diagnostic strategies in cancer
patients by identification of primary tumors and distant
metastases [37]. PET as metabolic image has been shown
to be potentially valuable for staging of various tumor
types, including breast cancer. FDG-PET has been shown
to be a more sensitive technique for the assessment of
chemotherapy responses because it is better at distin-
guishing cancerous tissue from necrotic and fibrotic tis-
sues and it reflects therapy-induced metabolic changes,
which are known to precede volumetric changes in a tu-
mor. The therapy-induced changes in tumor metabolism
may be helpful in making decisions about continuation,
modification, or cessation of chemotherapy [17,21].
Across all 19 studies, the pooled SEPET was signifi-
cantly higher than pooled SED (83.7% vs. 59.0%, p <
0.001), which resulted in higher detection rate of effec-
tive treatment. Pooled SPPET was higher than pooled
SPD (66.8% vs. 40.8%, p < 0.001), which resulted in
higher distinguishment rate of invalid treatment. Pooled
DORPET, AUCPET and Q*
PET were all significantly
higher than pooled DORD, AUCD and Q*
D (DOR:
14.017 vs. 1.288, p < 0.05; AUC: 0.8824 vs. 0.6046, p <
0.001; Q*: 0.8129 vs. 0.5788, p < 0.001). All results
suggested that reduction rate of glucose metabolic of
tumor tissues can be more accurately assess the effi-
ciency of NAC than that of reduction rate of tumor size
in breast cancer.
There are several limitations to our study. 1) The funnel
plots showed possible publication bias in both FDG-PET
and other examinations. To find source of this publica-
tion bias, we summarized the QUADAS criteria result of
the 19 studies. The total proportion of quality score was
81.58%, which suggested high quality. But the represen-
tative spectrum showed the lowest proportion of quality
score which is the unique score below 50%. Among 19
studies, six [16,17,19,21,23,24] included only invasive
ductal carcinoma (IDC) and invasive lobular carcinoma
(ILC), two [28,31] included only IDC and mucinous car-
cinoma, and one [32] included 108 IDC and 2 other kinds
of carcinoma. And in all articles that discribed represen-
tative spectrum, the proportion of IDC was far greater
than others, which may be the main reason for the publi-
cation bias. An important limit is that the pretreatment
SUV must be high in order to detect a meaningful reduc-
tion during treatment. Low contrast tumours are more
difficult to distinguish from background tissues and are
more affected by imaging imprecision. This requirement
limits the use of PET in patients whose tumours have low
initial FDG uptake, which is the case more important for
ILC [23,38]. ILC represents the second histological type
of breast cancer (almost 15%) after IDC (almost 80%).
ILC is a well-established source of weak FDG uptake [38]
and PET might not be suitable for early evaluation in this
subtype. The chemosensitivity of lobular carcinoma is
low [39,40]. Well-differentiated steroid receptor-positive
tumours can sometimes also be a source of low FDG
uptake. But there were not sufficient informations to
carry out a subgroup analysis of different subtype carci-

Meta-Analysis: 18 F-FDG PET or PET/CT for the Evaluation of Neoadjuvant Chemotherapy in Locally
Advanced Breast Cancer
670
noma or receptor expression; 2) The heterogeneity test
results were as follows: There was no heterogeneity for
FDG-PET except the test of SP, while heterogeneity for
other examinations except the test of DOR. There was no
conclusive evidence of a cutoff effect for FDG-PET to
Spearman correlation coefficients (p value < 0.4). But a
cut off effect was present for other examinations (p value
> 0.4). The existence of heterogeniety suggested the
needs for higher quality prospective studies and multi-
center trials. In this meta-analysis, Subgroup analyses
were performed to identify heterogeneity potential sources,
including PET timing points and cutoff values as me-
tabolical response criteria. Figure 5 suggested SE rose
and SP decrease gradually as time goes on. The best time
point was after the second cycle of NAC while DOR was
the highest. Figure 6 showed 40% - 45% was the best
cutoff value of SUVmax as metabolical response with
the highest DOR, especially for highest SP which will
avoid over-treatment during NAC. These results were
something different from those of Yuting Wang et al.
[41].
Since breast cancer is a heterogeneous disease with a
demonstrated in prognosis based on molecular pheno-
types, many researchers have attempted to perform risk
stratification and individualized treatment according to
molecular phenotypes and a few studies tried to find the
proof of which molecular phenotypes of breast cancer
interpret FDG-PET evaluation accuracy [28,30,31,33,34].
In this meta-analysis, we found a trend that ER negative
breast cancers had higher SE than ER positive, but lower
SP, which probably because of a higher baseline SU-
Vmax level [42] and lower metabolical response rate
(48.42% vs. 80.26%) in ER positive resulted in greater
SUVmax changes (62.95% vs. 45.00%) which leaded to
difficultly decided thresold value for metabolical re-
sponse criteria. Furthermore, lower pathological response
rate (12.39% vs. 49.05%) and lower metabolical re-
sponse rate in ER positive than in ER negative suggested
that the NAC effect is not obvious to ER positive, and
also reduced quality of PET image. Therefore, further
study will focus on research different criteria according
to molecular phenotypes for more accurate evaluation.
5. Conclusion
Based on the studies reviewed, FDG-PET does have a
higher global accuracy in assessing the NAC response in
breast cancer. It seems to be a more useful supplement to
current surveillance technique to reflect the histopa-
thologic results. Comparing with clinical response, me-
tabolical response plays a potential role in directing
therapy for breast cancer. In order to have better correla-
tion with pathological response, it’s suggested to perform
FDG-PET after second cycle of NAC and employ cutoff
value between 40% and 45% as FDG-PET criteria for
metabolical response. Furthermore, different criteria will
be drawn up according to molecular phenotypes in breast
cancer for individualizing examinations. With the devel-
opment of medical equipment and the improvement of
PET technology, it is important to collect more random-
ized studies, which can provide more useful information
for guidance clinical work.
6. Acknowledgements
This work was supported by Shanghai Leading Aca-
demic Discipline Project S30203.
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