risk factors for progression of cervical intraepithelial ...hybridization assay in a dot-blot format...
TRANSCRIPT
Servei d’Epidemiologia i Registre del Cancer, Institut Catal#{224}d’Oncologia,
Hospital Duran i Reynals. Ciutat Sanit#{224}riai Universit#{224}ria de Bellvitge. Autovia
de Castelldefels km 2.7 L’Hospitalet de LI. 08907 Barcelona, Spain [V. M.,
F. X. B.. S. d-S., P. V.1; Laboratori de BioestadIstica i Epidemiologia, Facultat
de Medicina, Universitat AutOnoma de Barcelona, Barcelona, Spain [V. M.J;
International Agency for Research on Cancer, Lyon, France [N. M.];
Delegaci#{243}n Territorial de Bienestar Social. Salamanca, Spain [L. C. G.j;
Universidad del Valle, Cali, Colombia [L. TI; Hospital Universitario del
RocIo, Sevilla, Spain [M. G.l: Registro de Cancer de Euskadi, Departamento
de Sanidad y Consumo. Gobierno Vasco, Vitoria-Ga.steiz, Spain [I. I.J;
ConsejerIa de Sanidad y Ausuntos Sociales, Murcia, Spain [C. NI; Registro de
Cancer, DiputaciOn General de Arag#{243}n,Zaragoza, Spain [A. V.1; Hospital
Santa Caterina. Girona. Spain [P. V.1; Departamento de Salud, Gobiemo de
Navarra, Pamplona, Spain IN. Al; and School of Hygiene and Public Health,
The Johns Hopkins University. Baltimore, Maryland 21218 [K. V. S.�
Received 10/17/94: revised 4/17/95; accepted 4/20/95� Financial support was received from the ARC, the European Community
[CI 1-0371-F (CD)l. the Fondo de Investigaciones Sanitarias of the SpanishGovernment (86/753. 87/1513, 88/2t)49, and 90/0901) and by the Spanish Mi-
nisterio de Educacion y Ciencia (PR94-053). We acknowledge the support re-ceived in Spain from the Health Departments of the Autonomous Communities
and from the local administrators in the areas that participated in the study.2 To whom all requests for reprints should be addressed.
Vol. 4, 459- 467, July/August 1995 Cancer Epidemiology, Biomarkers & Prevention 459
Risk Factors for Progression of Cervical Intraepithelial Neoplasm
Grade III to Invasive Cervical Cancer1
V.Moreno,2 N. Muiioz, F. X. Bosch, S. de Sanjos#{233},L. C. Gonzalez, L. Tafur, M. Gili, I. Izarzugaza,C. Navarro, A. Vergara, P. Viladiu, N. Ascunce, andK. V. Shah
Abstract
Data from four case-control studies on invasive cervicalcancer and on cervical intraepithelial neoplasia grade III(CIN III) that were concurrently conducted in Spain andColombia were used to look for factors that might favorthe progression from CIN III to the invasive stage. Thesestudies were compared in two ways: a case-casecomparison and an estimation of the ratio of odds ratioswith the use of a special logistic regression model thattook into account the different design of each study andpossible confounding factors. Variables studied werehuman papillomavirus status, viral load, viral types,sexual behavior, sexually transmitted diseases,reproductive patterns, oral contraceptives, and smoking.Both CIN III and invasive cervical cancer have a verysimilar profile of risk factors and none of them was
different in a consistent way to suggest a role in theprogression from CIN III to invasive cervical cancer.
Some methodological problems such as cohort-specificdifferences and some selection biases could be adjustedfor with a careful statistical analysis. Other problemsderived from the cross-sectional nature of the design are
unavoidable and should be considered in theinterpretation of the results.
Introduction
Several studies have been carried out to assess the naturalhistory of CIN3 in relation to its progression to ICC (1-3), butlittle is known about the factors that determine such progres-sion. The ideal design to address the problem would be a cohortstudy with ICC as an end point, but ethical reasons make suchstudies impossible. Any attempt at a longitudinal design mustend the follow-up when CIN III lesions (i.e., severe dysplasiaon carcinoma in situ) are found and treated. As an alternative,data from cross-sectional or case-control studies may proveuseful to look for factors that may determine the progression of
CIN lesions by comparing ICC cases with CIN III cases.We had the opportunity to explore this possibility using
data from four case-control studies, two on ICC and anothertwo on CIN III that were conducted in Spain and in Colombiaconcurrently. These two countries have an 8-fold difference in
the incidence of invasive cervical cancer. However, the esti-mated prevalence of CIN III among screened women appears tobe similar in both countries (4), which suggests that the differ-ence in incidence of invasive cancer could be due to a differentrate of progression of CIN III or to very different screeningstrategies. In this report, we compare the ICC and the CIN IIIstudies for each country, to look for differences in risk factors
that could be interpreted as progression factors. We also ad-dress the difficulties in the interpretation of this comparison dueto the nonlongitudinal design of the studies.
Materials and Methods
Study Population
The main results of these studies, concerning the role of HPVand other risk factors, have been published elsewhere (5-8).The design and the methods used have been described in detailin the main papers. In brief, the field work was conducted innine provinces in Spain (Alava, Girona, Guipuzcoa, Murcia,Navarra, Salamanca, Sevilla, Vizcaya, and Zaragoza) from
June 1985 to December 1987 and in the city of Cali in Colom-
bia from June 1985 to December 1988.
Cases
Eligible cases were, for the ICC studies, incident histologically
confirmed invasive squamous cell carcinomas of the cervixidentified among residents in the predefined study areas. All
cases of CIN III, (including severe dysplasia and in situ cancer)diagnosed during the study period were included in the CIN IIIstudies. Cases were identified by periodic visits to all hospitals,pathology laboratories, and screening clinics of each area.
3 The abbreviations used are: CIN, cervical intraepithelial neoplasia; ICC, inva-
sive cervical cancer; HSV, herpes virus; HPV, human papillomavirus; 5Th.sexually transmitted disease; OC, oral contraceptive; OR. odds ratio.
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460 Progression Factors in Cervical Cancer
Controls
Controls for the ICC studies were an age-stratified randomsample selected from the general population that generated thecases. The target number was 1 control/case. Individuals iden-tified as controls who were ineligible or untraceable werereplaced, but those who refused were not. For the CIN [IIstudies, 1 control/case was identified and matched by age (±5
years), place of recruitment, and date of cytology (± 1 day).Eligible controls should have had a normal or, at most, inflam-matory cytology (Papanicolaou grades I-Il).
Data Collection
Interviews. Study subjects were interviewed following a struc-tuned questionnaire that addressed education, socioeconomicstatus, lifetime sexual behavior, reproductive patterns, hygienicpractices, use of tobacco, oral contraceptives, and history ofsexually transmitted diseases.
Biological Specimens. All women participating were asked toprovide a blood sample to measure antibodies to some of the
common sexually transmitted agents (Neisseria gonorrhea,
Treponema pallidum, Ch!amvdia tracho,natis and HSV type 2;Ref. 9) and two cervical scrapes. With the first scrape, a smearwas prepared and stained by the Papanicolaou method, and
the remaining cells were pooled with the second scrape,eluted in PBS, pelleted, and stored at -20 or -70#{176}C. Formost cases, a fresh biopsy from the cancer was obtained andfrozen without processing. The histological slides (in whichthe original diagnosis was made) and the Papanicolaousmears taken at study entry were reviewed by a panel ofthree pathologists who reached a consensus diagnosis afterseveral reviews.
Detection of HPV DNA
The available cell samples were divided into aliquots whensufficient material was obtained and tested by several meth-
ods as reported earlier (10). In brief, samples were assayedinitially for HPV with Virapap (Digene Diagnostic, Inc.,Silver Spring, MD), a commercially available DNA-RNA
hybridization assay in a dot-blot format that screens for thepresence of HPV-DNA with a pool of 7 HPV probes (6, 11,16, 18, 31, 33, and 35). A second aliquot was used forSouthern hybridization in most of ICC cases and controls butonly in 40% of cases and I 1 % of controls of CIN III studies.Therefore, this method of HPV assessment has not been usedfor comparison of the diseases. Sixty % of the subjects
provided an aliquot to be processed for PCR with the use ofHPV-L1 consensus primers. The amplification productswere hybridized sequentially to end-labeled type-specificprobes of HPV 6, 1 1, 16, 18, 31, 33, and 35 under high
stringency conditions. Subsequently, the same filters werescreened with an HPV generic probe, which was a mixture ofamplimers of HPVs 16 and 18. Specimens positive only tothe generic probe were called “HPV-positive, undeterminedtype.” The results for HPV-DNA showed in the analysisrefer to the PCR assay since it had a greater sensitivity thanVirapap. Subjects without PCR results were grouped in adifferent category.
Statistical Analysis
The assessment of the differences in risk factors between the
CIN III and ICC cases was not trivial because they had beenascertained with different sampling schemes and data from an
unmatched study had to be compared with data from a matchedstudy. Although all incident cases of ICC in the study areaswere detected and population controls were used for compani-
son, detection of CIN III cases was based on screening practicesbecause most cases are asymptomatic. These CIN III patientswere younger and tended to be of higher education and socio-
economic status than was the general population. Thus, controlswere matched to the cases to minimize these differences. To try
to overcome the design limitations, two different analyses werecarried out. First, in a case-case comparison with the use oflogistic regression models, ICC cases were compared to CIN IIIcases (as a reference) with a very thin age stratification (in
5-year intervals) to adjust for the different age distribution.Education and other significant risk factors were also included
in the models to assess the differences between ICC and CIN IIIcases. This analysis could be interpreted as a hypotheticalcase-control study within a CIN [II cohort. We could imaginethat a hypothetical cohort of women with undetected CIN IIIwere followed and those that developed ICC were included in
the study as cases. Some women with CIN III persisted, andthey were captured as controls if they were screened. Those
that regressed to a normal cervix and those that were notscreened were lost from the cohort. Thus, we would be
comparing ICC to a sample of persistent CIN III. In thishypothetical context, the sample of CIN III cases used in ourstudy would be biased, mainly in Spain, with respect to ageand education because it has been drawn from a differentcohort of women who are younger and better educated thanICC cases.
The second approach was a comparison of the relative riskestimates for selected risk factors, taking into account therespective controls of each disease group. Cases and controls
from the CIN III and the ICC studies were analyzed togetherwith the use of a unique model that took into account thedifferent design of each study (11). The model mixed a condi-tional logistic regression likelihood function for the CIN III
cases and controls and an unconditional logistic regressionlikelihood function for the ICC group. This was fitted easilywith the GLIM package (12), because for the 1 case:1 controlmatching design of the CIN III study, the conditional logisticregression likelihood can be written as a unconditional lo-
gistic regression likelihood function if we calculate for eachvariable the difference between the case and the control ineach set. For the comparison of CIN III with ICC, the interac-tion terms between the risk factors of interest and an indicatorvariable that defined the disease group (CIN Ill/ICC) wereused. The coefficients for these interaction terms estimate thedifferences (in log odds ratio scale) for a risk factor between
both diseases. By exponentiating these coefficients, the ratioof ORs can be estimated. This model assures that each group ofcases is compared with its own control population; thus, the
main concern about cohort-specific differences between theCIN III and the ICC groups are adjusted for with this methodof analysis. The model also allows for the estimation of the ORratios adjusted by potential confounding factors such as age,
education, and other variables that were significant risk factors
for CIN III or ICC.
Results
Recruitment. A total of 436 patients with ICC agreed toparticipate (250 in Spain and 186 in Colombia). Populationcontrols (387) were recruited for these cases (238 in Spainand 149 in Colombia). The proportion of refusals in Spainwas 11.5% among cases and 26.2% among controls and in
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Cancer Epidemlology,Biomarkers & Prevention 461
Colombia it was 16.0% among cases and 19.8% amongcontrols. For the CIN III study, a total of 390 cases wereincluded for the analyses (182 in Spain and 208 in Colom-
bia). Cases (55) and their matched controls were excluded
because the panel of cytopathologists reclassified them as
CIN I-Il. Eight cases were excluded because a matchedcontrol could not be found. The proportion of refusals was7.4% among cases and 19.7% among controls in Spain and
0.7% among cases and 19.3% among controls in Colombia.The number of cases with ICC was lower than the number of
controls because 72 cases (42 in Colombia and 30 in Spain)
initially classified as CIN III were upgraded to ICC after thepanel review.
Sociodemographic Factors. As shown in Table 1, cases withICC were, on average, 16.5 and 8.3 years older than were caseswith CIN III in Spain and Colombia, respectively (P < 0.001).
Cases with ICC from Colombia were 5.7 years younger thanthose from Spain (P < 0.001), while CIN III cases fromColombia were 2.5 years older than those from Spain (P <
0.05). CIN III cases in Spain were recruited largely from family
planning centers because there was no established screening
program in Spain like in Colombia, where most CIN III caseswere recruited from screening clinics. The age distribution of
the CIN III and ICC cases overlapped substantially in Colombia
but not in Spain (Fig. 1), which complicated the case-casecomparison. These age differences became less problematicwhen controls of each group were taken as baseline for risk
estimation because controls had been chosen to have the sameage distribution as the cases. Cases tended to be less educatedthan were controls, and ICC cases and controls were less
educated than were those cases and controls with CIN IIIin both countries. This latter difference was more important in
Spain and was probably due to the sum of a cohort effect(younger women have had better access to education) and someselection bias because women who attend screening or family
planning centers are, in general, more educated. In Colombia,
the difference between CIN III and ICC in education was notsignificant when age was taken into account. Income showed
the same pattern as education and was not considered furtherbecause it was a correlated marker of socioeconomic status. In
general, most established risk factors for CIN III and ICC were
more prevalent in Colombia than in Spain. Colombia womenwith ICC had a higher number of partners, earlier age at first
sexual intercourse, higher parity and prevalence of oralcontraceptive use, smoking, and STDs other than HPV.Differences between countries in women with CIN [II fol-lowed a similar pattern to those of ICC except for smokingand oral contraceptive use, which were more prevalent
among Spanish women.Table 2 shows the results for main risk factors in the
case-case comparison. For each country and the combination of
both, the odds ratio and 95% confidence intervals adjusted for
all significant factors are presented. Tables 3, 4, and 5 presentthe odds ratios and 95% confidence intervals for each diseasegroup with respect to their own controls and the OR ratios
estimated from the combined model. For the CIN III group,some of these odds ratios may differ slightly from those pub-
lished previously because here the sample size was smaller and
a conditional logistic regression analysis has been used. Thisconditional logistic regression is the proper way to analyzematched studies because it ensures that each case is comparedwith its own matched control.
HPV Type and Viral Load. HPV infection was found tobe the most important risk factor for both CIN III and ICC in
these case-control studies. Odds ratios in Spain were 137.4 forCIN III and 51.9 for ICC and in Colombia they were 17.4for CIN III and 15.9 for ICC. This differences among thecountries were essentially due to the HPV-DNA prevalence
among controls, which was three times higher in Colombia.
However, HPV infection itself could not explain the progres-sion from CIN III to ICC, since the risk was similar for both
type of cases in each country. We looked into the possibilitythat specific HPV types might be more associated with pro-gression. Type 16 was found to be the most prevalent both in
ICC (66% in Spain and 69.9% in Colombia) and CIN III(69.4% in Spain and 51.9% in Colombia). The other HPV-
positive cases were distributed homogeneously among viral
types 18, 31, 33, and 35. The proportion of cases with HPV-DNA of undetermined type was higher in CIN III than in ICCcases from Colombia (38 versus 9.5%; P < 0.001). The dis-tnibution of HPV types among controls resembled that of thecases, but the prevalence of HPV-DNA was too low to allow forrisk comparisons. Viral load was crudely estimated by grouping
the patients in three categories according to the hybridizationmethod that evidenced the presence of HPV-DNA. The refer-
ence category was those that were negative for HPV in the three
assays; low viral load was considered when only PCR de-tected HPV, and high viral load was considered when Vira-
pap or Southern hybridization methods were positive alsobecause these are known to be less sensitive and need thepresence of a higher viral load to give positive results. No
differences were found between the groups. Other viral loadestimates, the Virapap score, were also considered showing
similar results.
Sexual Behavior. The distribution of the number of sexualpartners was similar in both groups of cases, but in the case-
case comparison, once adjusted for possible confounders, thisfactor appeared moderately associated with a 2-fold increase forinvasive cancer as compared to CIN III in both countries. The
OR ratio estimates also showed a similar result, mainly inColombia, since the odds ratio for ICC was 2.6 times that for
CIN III, although this was not statistically significant. The age
at first sexual intercourse was an important risk factor for bothCIN III and ICC but the comparison indicated that it was notclearly related to the progression from CIN III to ICC.
Sexually Transmitted Diseases. Among the STDs studied,HSV 2 was the most prevalent, followed by Chiamydia tra-
chomatis and Neisseria gonorrhea: Syphilis was very rare inSpain, and in Colombia the prevalence of this infection was
< 10%. All STDs were more prevalent among cases thanamong controls. Neisseria gonorrhea was a risk factor for CINIII and ICC only in Spain, but the OR ratio was not significantly
different from 1. In Colombia, the case-case comparisonshowed a nearly 2-fold increase of risk of progression. C/i/a-mydia trachomatis was a risk factor for CIN III only and the OR
ratio was 0.4 with respect to ICC. In the case-case comparison,however, no association for Chiamydia trachomatis was ob-served, and this reflected the very similar prevalence of this
infection among cases. No associations were observed for otherSTDs studied (Treponema pallidum and HSV 2) in either of the
two types of analysis.
Reproductive Patterns. Parity, defined as the number of livebirths, was greater in Colombia than in Spain (mean of 3.8versus 2.1 children in CIN III cases; P < 0.001 and 5.4 versus
3.1 children in ICC cases; P < 0.001). The comparison of CIN
III versus ICC was difficult because parity was very related toage and, as stated before, the group of CIN III subjects wasmuch younger than the group of ICC subjects. The case-case
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Table I Prevalence of the main risk factors by country and study group
Colombia Spain
CIN Ill ICC CIN Ill ICC
Cases Controls Cases Controls Cases Controls Cases Controls
Subjects 208 208 186 149 182 182 250 238
38.2 38.5 46.5 47.5
11.7 11.8 12.7 12.4
35.9 52.2 52.3
8.3 12.7 12.5
8.7 3.8 16.7 6.0 7.7 10.4 32.8
59.1 54.3 66.7 67.8 58.8 57.1 55.6
32.2 41.8 16.7 26.2 33.5 32.4 11.6
31.7 58.2 22.0 30.2 61.0 70.9 40.8
40.9 24.0 21.0 26.2 34.1 23.6 37.6
27.4 17.8 57.0 43.6 4.9 5.5 21.6
Oc’ use (%)
Never
Ever
38.0
62.0
90.6
9.4
94.5
5.5
91.2
8.8
96.4
3.6
92.0
8.0
46.6 58.2 40.9 58.4 62.1 81.9 75.6
39.4 36.5 41.4 38.9 26.4 17.0 19.2
13.9 5.3 17.7 2.7 11.5 1.1 5.2
50.0 65.4 48.9 60.4 39.0 53.3 73.6 83.2
50.0 34.6 51.1 39.6 61.0 46.7 26.4 16.8
17.3 54.3 12.9 57.0 20.3 76.4 17.6 52.1
33.7 7.7 33.9 8.7 48.9 3.3 39.2 2.5
49.0 38.0 53.2 34.2 30.8 20.3 43.2 45.4
62.5 72.6 48.4 66.4 81.3 80.8 75.2 81.9
22.6 15.4 31.7 22.1 14.8 8.2 12.0 1.7
14.9 12.0 19.9 11.4 3.8 11.0 12.8 16.4
I pallidiini (%)
Negative
Positive
Unknown
39.4 64.4 37.6 51.7 67.6 77.5 63.2 69.7
42.3 22.1 38.2 35.6 26.9 9.9 23.2 13.4
18.3 13.5 24.2 12.8 5.5 12.6 13.6 16.8
26.4 36.5 17.2 26.8 61.5 61.5 48.4 50.0
63.5 54.8 66.1 66.4 35.2 28.6 40.4 34.9
10.1 8.7 16.7 6.7 3.3 9.9 11.2 15.1
462 Progression Factors in Cervical Cancer
Age
Mean
SD
Education (%)
None
Primary
Secondary
Parity (%)
0-2
3-4
5+
History of caesarean section (%)
Never 89.9
Ever 10.1
89.9 96.2
10.1 3.8
35.7
8.2
22.7
60.1
I 7.2
57.1
31.1
11.8
35.6 58.1 63.1 31.3 44.5 74.4 77.3
64.4 41.9 36.9 68.7 55.5 25.6 22.7
Age at first sexual intercourse (%)
20+ 25.0
18-19 17.8
16-17 25.5
<16 31.7
No. of sexual partners (%)
Monogamous
2-5
6+
Smoking (%)Never
Ever
HPV-DNA status (%)
Negative
Positive
Unknown
N. gonorr/:oeae (%)
Negative
Positive
Unknown
C. traeho,natis (%)
Negative
Positive
Unknown
Herpes virus 2 (%)
Negative
Positive
Unknown
38.0 23.7 38.3 52.7
26.4 18.8 19.5 28.0
21.2 25.8 24.8 14.3
14.4 31.7 17.4 4.9
76.0 81.7 69.9 81.9
9.1 6.3 10.2 6.7
14.9 12.0 19.9 11.4
73.1 66.8
16.5 19.6
9.9 10.0
0.5 3.6
84.5
11.8
2.9
0.8
91.6
6.7
I .7
95.1 88.5 83.6 83.2
1.1 0.5 3.6 0.4
3.8 11.0 12.8 16.4
“ OC, oral contraceptive.
comparison revealed, after adjustment for age, education, andother important risk factors, a greater parity in [CC than in CIN
III for both countries, although the trend was not significant.The comparison of the OR estimates for each group withrespect to their controls showed a different pattern. In Spain, the
risk was much greater in the ICC group than it was in the CINIII with an OR ratio of 12.5. On the other hand, in Colombia
this ratio was 0.37 with an opposite direction and was alsosignificant.
Caesarean section appeared as a more protective factor for
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Spain
%
Table 2 CIN Ill/ICC case-case comparison
.Colombia
.Spain
(‘olombia.
and Spain
OR” (95% Cl”) OR” (95% CI) OR” (95�% Cl)
Education
Age (years)
Colombia OC use
Age (years)
None lOt) 1(M) 1.00
Primary 1.08 (0.53-2.22) 0.29 (0.1 1-0.74) 0.62 (0.35-1.11)
Secondary 0.78 (0.32-1 .85) 0.26 (0.09-4)79) 0.48 (t).25-0.95)
Parity
0-2 1.00 1(5) l.()()
3-.4 0.61 (0.33-1 . 13) 1 . I I) (0.58-2.08) 0.8 1 (0.53-1.25)
5+ 1.50 (0.79-2.85) 2.42 (0.84-6.99) 1.82 (1.07-3.07)
P 0. 14 0. 18 0.05
History of caesarean section
Never 1.00 lOt) 1.00
Ever 0.37 (0.14-4)95) 1.03 (0.28-3.75) 0.53 (0.25-1.11)
Never 1.00 1(X) 1(X)
Ever 0.92 (0.53-1.61) 0.67 (0.34-1.31) 0.82 (0.54-1.25)
Age at first sexual intercourse
211+ lOt) 1(X) 1(X)
18-19 1.18 (0.58-2.37) 1(14 (0.49-2.22) 1.14 �).69-l.88)
16-17 1.20 �).62-2.33) 1.94 (0.76-4.95) 1.34 (1)79-2.26)
<16 1.27 (0.63-2.55) 0.52 (0.10-2.68) 1.12 (0.62-2.1)4)
P. 0.51 1)59 0.50
No. of sexual partners
monogamous 1.00 1 .00 1 IX)
2-5 1.32 (0.78-2.21) 1.4)) (0.68-2.87) 1.26 �).84-1.90)
6+ 1.77 (0.89-3.55) 2.68 (0.87-8.30) 1.87 (1.05-3.34)
P 0.09 0.09 1)03
Smoking
Never 1(X) 1(X) 1.01)
Ever 0.96 (0.60-1.52) 1.49 (0.73-3.1)5) 1.1)6 �).73-1.53)
HPV-DNA status”
Negative I .01) 1 IX) I IX)
Positive 1.44 (0.70-2.96) 0.99 (0.45-2.18) 1.15 (0.69-1.93)
N. gonorrhoeae”
Negative 1.01) 1(X) 1(X)
Posilive 1.68 (0.98-2.89) 1.23 (0.55-2.76) 1.48 �).96-2.31)
T. pall#{252}luin”
Negative 1(X) 1(X) 1(X)
Positive 1.15 (0.53-2.53) 3.61) �).4l-3l.44) 1.37 (0.66-2.85)
C. Irac/iornati.s-’1
Negative 1(X) 1(X) 1.01)
Positive 0.99 (0.59-1.67) 1(X) �).5l-l.98) 1(X) (0.67-1.51)
Herpes virus 2”
Negative 1.00 1.15) 1.01)
Positive 1.27 (0.72-2.25) 1.35 �).72-2.54) 1.28 �).85-1.94)
CIN Ill Eicc
Fig. 1. Age distribution among cases of CIN III and ICC in Spain and
(‘otombia.
ICC than for CIN III, but this was only statistically significantfor the case-case comparison in Colombia.
OCs. Oral contraception was not found as a risk factor for
CIN III or ICC in these populations. Neither the comparison ofboth groups of cases nor the OR ratio estimate showed any
association.
Tobacco. Smoking was a minor risk factor for both CIN IIIand ICC, but the prevalence among cases and odds ratios weresimilar either when smoking was considered as ever/never orwhen estimated pack-years were compared.
Discussion
This analysis was aimed to increase our understanding of the
natural history of cervical cancer and specifically to look forfactors that might favor the progression from CIN III to theinvasive stage. Several investigators have studied CIN III andICC and presented risk estimates separately for each group of
cases but, to our knowledge, this is the first formal statisticalcomparison of both groups. We used the information gatheredfrom four case-control studies on ICC and on CIN III that wereconducted in Spain and in Colombia concurrently and com-pared them in two ways: (a) differences in the prevalence of themain risk factors among the cases of CIN III and ICC were
evaluated, ignoring the control groups; and (b) ratio of ORs forthe CIN III and the ICC case-control studies were estimated foreach factor. The interpretation of the results should take into
(‘ Models always included age, center. education, parity, history of cesarean
section. age at first sexual intercourse and no. of sexual partners.
S CI, confidence interval; OC. oral contraceptive.
‘- Trend test P value.
,! Missing values coded in a different category (not shown).
account several aspects. Biases that are commonly involved in
case-control studies (recall, interviewer, refusal, referral, etc.)may occur in one study but not in another, or they may occurat a different magnitude. Differences or indifferences in oddsratios could be due to different biases involved and havenothing to do with progression. The design and execution of
the studies have tried to minimize these possible biases, hutobservational studies can rarely completely exclude theirexistence.
Cancer Epidemiology, Biomarkers & Prevention 463
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Table 3 Comparison of risk factors for CIN III and ICC in Colombia
CIN Ill ICC OR ratio
OR” (95% CI”) OR (95% Cl) ORR (95% CI)
Education
None
Primary
Secondary
Parity
0-2
3-4
5+
P
1.00
0.31
0.24
1(5)
3.49
5.05
O.(XX)8
Table 4 Comparison of risk factors for CIN III and ICC in Spain
CIN III ICC OR ratio
OR” (95% Cl5) OR” (95% CI) ORR” (95% CI)
1.01)
(0.08-1 . 1 8) 0.34
(0.06-1.07) 0.34
1.01)
(1.61-7.55) 1.39
(1.75-14.54) 1.53
0.25
1.00
(0.13-0.88) 0.92 (0.21)4.28)
(0.11-1.01) 1.24 (0.22-7.07)
1.00
(0.65-2.94) 0.39 (0.14-1.09)
(0.75-3.12) 0.37 (0.11-1.16)
0.035
Education
None
Primary
Secondary
Parity
0-2
3-4
5+
P
Abortions
Never
Ever
1.00 1.00 1.00
1.38 (0.38-4.95) 0.50 (0.28-0.91) 0.36 (0.11-1.25)
1.23 (0.28-5.40) 0.36 (0.16-0.83) 0.26 (0.06-1.12)
1.00 1.00 1.00
0.97 (0.37-2.57) 2.53 (1.50-4.25) 2.16 (0.82-5.70)
0.24 (0.03-1.68) 3.18 (1.59-6.37) 12.51 (2.03-77.04)
0.28 0.0001 0.02
1(X)
0.32
Age at first sexual intercourse
20+
18-19
16-17
<16
P
1.00
0.55
I .36
1.52
0.16
1.00
0.48
OC use
Never
Ever
1.00
1.43
3.24
3.37
0.012
(0.75-2.70)
(1.17-9.00)
(0.51-22.07)
1.15)
2.52
1.00
0.98 (0.33-2.90)
0.68 (0.12-3.78)
0.35 (0.02-7.92)
0.53
1.00 1(10
2.13 (0.81-5.57) 3.36
1.89 (0.31-11.54) 3.65
0.13 0.002
Smoking
Ever
Never
1.00 1.00
(0.23-1.29) 1.11 (0.52-2.35) 1.63 (0.55-4.84)
(0.58-3.15) 1.62 (0.77-3.39) 0.91 (0.32-2.61))
(0.59-3.96) 2.14 (0.95-4.85) 1.01 (0.33-3.11)
0.05 1)76
1.01) 1.00
(0.56-2.07) 1 .20 ((1.68-2. 12) 1 . 11) (0.49-2.46)
(1.04-8.37) 6.95 (1.97-24.56) 2.56 (0.53-12.44)
0.01)9 0.47
1(5) 1.01)
(1.36-4.69) 1.39 (0.81-2.40) 0.62 (0.28-1.36)
1.01) 1.01)
(6.41-47.34) 15.86 (7.02-35.83) 0.99 (0.29-3.34)
1(X) 1.01)
(0.56-2.61) 1.05 (0.54-2.03) 0.85 (0.33-2.20)
1.0(1 1.01)
(0.2 1-1 .9 1 ) 1 .33 (0.47-3.73) 1.62 (0.38-6.87)
1.00 l.()0
( I . 15-5.30) 0.86 (0.47-1 .59) 0.40 (0.16-1.00)
1.00 1.00
(0.38-1.47) 0.97 (0.49-1.91) 0.95 (0.39-2.31)
1.01)
1.21
1.15)
0.63
1(X)
2.47
1.00
0.74
1.00 1.00
Positive 137.39 (17.5-1078.)51.85 (20.22-132.9) 0.35 (0.04-2.95)
1.00 1.00
9.32 (1.52-57.09) 10.91
T. pallidurn”
Negative
Positive
C. trachoinatis”
Negative
Positive
Herpes virus 2d
Negative
Positive
“ All models included age, education, parity, age at first sexual intercourse, no. of
sexual partners, smoking, and HPV-DNA status.
S CI, confidence interval; ORR, ratio of odds ratios; OC, oral contraceptive.
‘� Trend test P value.
‘, Missing values in a separated category (not shown).
1.00 1.00
7.28 (1.3(1-40.73) 1.51
1.00 1.00
1.11 (0.47-2.61) 1.18
“ All models included age, education, parity, age at first sexual intercourse, no. of
sexual partners, smoking, and HPV-DNA status.
b CI, confidence interval; ORR, ratio of odds ratios; OC, oral contraceptive.
‘. Trend test P value.d Missing values in a separated category (not shown).
464 Progression Factors in Cervical Cancer
Abortions
Never 1 .01) 1.00
Ever 0.70 (0.39-1.29) 0.80
History of caesarean section
Never
Ever 1.01 (0.37-2.79)
OC use
Never 1 .00 1 Of)
Ever 0.87 (0.41-1.85) 1.09
No. of sexual partners
monogamous 1.00
2-5 1.07
6+ 2.96
P. 0.1)9
Smoking
Never
Ever
HPV-DNA status”
Negative 1(X)
Positive 17.42
N. ,i�),iorrhoeae”
Negative
Positive
71 i�allidu,fl”
Negative
Positive
C. traelio,natis”
Negative
Positive
Herpes virus 2”
Negative
Positive
1.00
(0.46-1.39) 1.13 (0.52-2.45)
1(5)
(0.09-I .09) 0.22 (0.()4-l .05)
1(5)
(0.58-2.03) 1.28 (0.51-3.21)
1.00 1.00
0.83 (0.34-1.99) 1.18
History of caesarean section
Never 1.00
Ever 0.60 (0.13-2.69)
1.00 1.00
1.99 (0.72-5.53) 0.81
Age at first sexual intercourse
20+ 1.00
18-19 2.41 (0.76-7.63)
16-17 7.34 (1.39-38.89)
<16 19.96 (1.18-336.2)
P. 0.002
No. of sexual partners
monogamous
2-5
6+
P
HPV-DNA status”
Negative 1.00
N. gonorrhoeae”
Negative
Positive
1.00 1.00
1.57 (0.62-3.95) 1.70
1.00 1.00
97.36 (0.63-4981.) 6.18
1.00
(0.71-1.95) 1.93 (0.78-4.79)
1.00
(0.19-1.24) 0.63(0.13-3.13)
1.00
(0.42-1.53) 0.41 (0.14-1.17)
1.00
(1.59-7.12) 1.37 (0.47-4.00)
(0.92-14.51) 1.03 (0.12-9.24)
0.27
1.00
(0.89-3.26) 0.85 (0.32-2.26)
1.00
(3.24-36.79) 2.92 (0.50-17.12)
1.00
(0.63-60.09) 0.43 (0.01-16.31)
1.00
(0.81-2.81) 0.36 (0.09-1.45)
1.00
(0.71-1.95) 0.93 (0.38-2.29)
The main concern about the comparability of the studiesrefers to the age distribution. We dealt with two differentcohorts of women, with an age lag of 8 years in Colombia and
16 years in Spain. Some differences found might be attributedto this cohort effect; thus, the adjustment for the potential
confounding of age was very important. The two methods of
analysis addressed the adjustment differently. The case-casecomparison used a thin age stratification in the logistic regres-sion models. For the comparison of risk estimates with the ORratios, each study group used their respective control popula.
tion that had been chosen to have the same age as the cases. Thus,the difference between both methods was the use of controls as a
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Table 5 Comparison of risk factors for
and Spain
CIN Ill
CIN III and ICC
ICC
in Colombia
OR ratio
OR” (95% Cl”) OR” (95% CI) ORR” (95% CI)
Education
None
Primary
Secondary
Parity
0-2
3-4
5+
P.
Abortions
Never
Ever
1.01)
0.74
0.72
1.00
1.96
2.05
0.027
1.00
0.66
1.01)
(0.32-1 .70) 0.42
(0.28-1.86) 0.35
1.00
(1.14-3.38) 1.81
(0.87-4.82) 1.91
0.0007
1.00
(0.41-1.05) 0.94
1.00
(0.26-0.67) 0.59 (0.23-1.47)
(0.19-0.65) 0.51 (0.18-1.49)
1.00
(1.21-2.71) 0.96 (0.51-1.83)
(1.22-3.01)) 1.07 (0.44-2.60)
0.96
1(X)
(0.66-1.34) 1.40 (0.80-2.45)
History of caesarean section
Never 1.00 1.00
Ever 1.02 (0.47-2.22) 0.40
OC use
Never
Ever
1.01) 1.01)
1.11 (0.66-1.89) 1.02
Age at first sexual intercourse
20+ 1.00
18-19 1.27 (0.70-2.31)
16-17 2.49 (1.26-4.90)
<16 3.59 (1.59-8.10)P. 0.001)7
1.00
1.29
1.67
I .87
0.012
(0.81-2.07)
(0.97-2.87)
(0.97-3.62)
1.00
1.08 (0.52-2.23)
0.75 (0.33-1.71)
0.67 (0.26-1.75)
0.56
1.00
(0.80-2.19) 1.64
(1.17-6.62) 4.65
0.0001
1.00
(1.07-2.52) 1.06 (0.57-1.97)
(1.93-11.19) 1.33 (0.40-4.42)
0.58
No. of sexual partners
monogamous 1.01)
2-5 1.33
6+ 2.79
P 0.021
Smoking
Ever 1.00
Never 2.19
HPV-DNA status”
Negative
Positive
N. gonorrhoeae”
Negative
Positive
T. jalliduni”
Negative 1(10
Positive 0.97
C. ��(J(./1�),7�(1(1#{231}d
Negative 1.00
Positive 2.69
Herpes virus 2”
Negative I .00
Positive 1.02
1.00 1.00
(1.37-3.50) 1.46 (0.99-2.14) 0.67 (0.37-1.21)
1.00 1.00 1.00
28.22 (13.07-60.96) 25.79 (14.61-45.5 1) 0.98 (0.39-2.48)
1.00 1.00 1.00
1.72 (0.91-3.25) 1.64 (0.97-2.77) 0.96 (0.44-2.12)
1.00
(0.32-2.92) 1.49
1.00
(0.63-3.50) 1.50 (0.40-5.64)
1.00 1.00
(1.44-5.03) 1.02 (0.68-1.54) 0.40 (0.20-0.82)
1.00 1.00
(0.64-1.64) 0.95 (0.65-1.39) 0.86 (0.48-1.55)
“ All models included age, education, parity, age at first sexual intercourse, no. of
sexual partners. smoking, and HPV-DNA status.1� CI, confidence interval; ORR, ratio of odds ratios; OC, oral contraceptive.‘. Trend test P value.
�, Missing values in a separated category (not shown).
reference for comparisons, and differences in the prevalence of the
risk factors between the controls of each group might explainmany of the discrepancies in the results shown by the two methodsof analysis.
Case selection bias was not a great problem for ICCstudies because an effort had been made to find all incident
Cancer Epidemiology, Blomarkers & Prevention 465
cases in the areas of study and because the disease is generallysymptomatic. However, case selection bias cannot be excluded
for CIN III studies. CIN III cases can rarely be ascertainedcompletely because this is an asymptomatic disease that only
can be diagnosed through screening practices, and womenattending screening clinics tend to be more educated and havehigher socioeconomic status. To adjust for these differences,the controls used for CIN III studies were selected to match the
characteristics of the cases.There is sufficient epidemiological evidence supporting
the idea that CIN is a dynamic disease, with some cases re-gressing spontaneously and others progressing to the invasive
state. However, the rate of progression to ICC is not preciselyknown. Old studies (13) indicate that untreated CIN III lesionsprogressed at the rate of 4.2%/year; thus, 50% of the womenwith cervical precancerous lesions had progressed to evident
invasive cervical cancer after 16 years of follow-up. A recentstudy based on women diagnosed with CIN III during 1967-
1.00 1977 who escaped treatment has found that 74% of them had(0.19-0.85) 0.39 (0.14-1.11) progressed to ICC (14). Most recent studies have only followed
up women with milder lesions, and for ethical reasons, the
1.00 information about progression to ICC comes from women that(0.66-1.57) 0.90 (0.47-1.74) develop the disease even after treatment has been applied. In
recent reviews (15, 16) it was concluded that global progressionfrom CIN III to ICC occurs in more than one-third of the cases,
another one-third of cases regress to milder lesions, and theremaining cases would persist in the same status for a long time.
The true rate is probably closer to those found in the earlystudies and, nowadays, is impossible to know because active
treatment of CIN lesions completely modifies the disease evo-lution. We face, thus, a considerable degree of misclassificationin the CIN III group. Ideally, CIN III cases that never pro-gressed to ICC should be compared with ICC, but about 36%
of CIN III cases would progress to ICC if left untreated, andthese are likely to have similar characteristics to the ICC cases.
This misclassification results in an attenuation of the differenceestimates, and a subsequent loss of statistical power to detectprogression factors that might explain some of the negative
results found in this study.From a statistical point of view, we should also take into
account that the comparison of risk estimates testing the sig-
nificance of interaction terms is a less sensitive method than thecase-case comparison. Most of the factors studied showed a
high relative risk for both CIN III and ICC diseases, and thesample size of the studies did not permit the detection ofsignificant interactions unless they were of great magnitude.We think, however, that this method of comparison addressedbetter the adjustment for cohort differences between the twogroups because the modeling allowed the subtraction out of
baseline differences: those between the control groups. How-
ever, a further methodological limitation still remained; be-cause only <15% of the controls were HPV positive, theadjustment by HPV status was not very efficient, and the riskfactors for HPV-DNA detection were impossible to separatefrom risk factors for development of CIN III and progression to
ICC.Our analysis showed that, although HPV infection was the
most important risk factor for CIN III and ICC, the prevalenceofthis infection was very similar in both groups and it could notbe considered a progression factor. HPV infection is probablynecessary for the development of both CIN III and ICC butother factors should contribute to the progression of the disease.
Some authors have suggested that high viral load is a betterpredictor of progression to CIN III (17). We have explored thishypothesis, but our indirect and crude methods for quantifying
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466 Progression Factors in Cervical Cancer
viral load, based on the hybridization tests, showed negative
results. Similarly, there was no evidence that specific types ofHPV were involved in the progression. However, for the inter-pretation of our HPV results we should bear in mind that 40%of the subjects could not be tested for HPV-DNA with aPCR-based assay. Also, when this assay was done, only prim-itive PCR techniques were available, and they were not assensitive as actual methods that have demonstrated that most
cervical cancers are HPV positive (18). The probability of a
specimen to be evaluated for HPV with PCR depended only onavailability of remaining cells after other hybridization tests hadbeen done and it did not differ according to study, country, or
case status. This minimizes the possibility that the negativeresults could be explained by differential bias (HPV-positive
CIN III cases providing sample at greater extent than ICCHPV-positive ICC cases).
Sexual behavior is a determinant of HPV infection, and thenumber of sexual partners can be considered a surrogate for theprobability of infection by HPV. Thus, it may be reasonable
that the association found with this variable showed residualmisclassification of the HPV-negative cases, many of whichreally were HPV positive. Age at first sexual intercourse is
another risk factor for CIN III and ICC that is frequently
reported. Some studies find that this effect disappears whenadjusting for the number of sexual partners, whereas others findboth variables independent. Although age at infection is un-
known, it might be correlated with age at first sexual inter-course or the probability of infection might be greater at earlyage (6, 7). Age at first sexual intercourse was very differentbetween subjects in Spain and Colombia, and may be alsorelated to the difference in the age at diagnosis of ICC becausethe period from first intercourse to diagnosis for both countrieswas very similar, approximately 30 years on average. Weshould note that in Spain the sexual behavior pattern changed
during the last few decades, and we could be observing animportant cohort difference when CIN III with ICC case and
control groups are compared.The role of sexually transmitted diseases other than HPV
in the development of ICC remains unclear. Serological assaysfor some of these infections such as Neisseria gonorrhoeae andChlarnvdia trachomatis have relatively low sensitivity andspecificity. ChIa,nvdia trac/zoinatis appeared as a risk factor for
CIN III but not for ICC, although prevalence among cases wassimilar. The discrepancy between the results of both methods ofanalysis was due to the low prevalence among CIN III controls.
Because these controls were selected from screening or familyplanning clinics, they could be healthier than the general pop-ulation of their age group, and this selection bias would explainthe difference. HSV-2 was the most prevalent infection, but its
prevalence was similar in cases and controls both for CIN IIIand ICC. Parity has been repeatedly related to cervical cancer(19-20) and CIN III lesions (21-22). However, similar to the
results obtained in this comparison, the role of this factorremains unclear because of a lack of consistency between the
different studies.The main conclusion of this study is that CIN III and ICC
have a similar profile of risk factors; HPV infection is the mostimportant. None of the risk factors studied showed consistentdifferences between CIN III and ICC, and this overall negativeresult suggests that either progression is just a matter of timeand chance, or other mechanisms not studied, like host factors(immunological response or genetic susceptibility), or unknownviral properties may play an important role. The most clear
difference between CIN III and ICC cases was age at diagnosis.
The age distribution of CIN III cases showed a fast increase (up
to a maximum at around 30 years) and then decreased, also ata fast rate. For ICC cases, the distribution was shifted towardolder ages and had a flatter appearance. These curves are
compatible with an initial pool of CIN III cases determinedmainly by HPV infection. Some of these cases would progressto the invasive state by chance accumulation of several Un-known hazards, whereas other cases would regress spontane-ously. At the molecular level, virological studies have shown
that the HPV-DNA is generally maintained in an episomal statein CIN lesions while integration of the HPV-DNA into thecellular genome is more frequent in ICC, especially for HPV
type 18 (23). This integration of HPV into the cellular genomeusually disrupts the El or E2 open reading frames and thiscould lead to a deregulation of the E6 and E7 genes that havebeen involved in the immortalization of the human keratino-cyte. Although integration could be a random process, mainlyrelated to time, some factors could favor it. Also, other impor-tant aspects to consider could be the site of integration andpossible gene mutations. Some immunological studies haveshown that the expression of the MHC is altered in the cells ofCIN III and ICC lesions. The expression of MHC class I,related with the presentation of endogenous antigen to cytotoxic
T-lymphocytes, is severely diminished. Simultaneously, theexpression of MHC class II, related with the presentation ofexogenous antigens to T-helper cells, is upregulated. These two
disturbances of the MHC may provide the neoplastic cell witha mechanism to escape immune surveillance. However, therelationship of these alterations with HPV infection is not veryclear yet (24). Future epidemiological studies should incorpo-rate new markers to elucidate the role of these mechanisms.
Acknowledgments
We thank Drs. Mark Schiffman, Norman Breslow, Valerie Beral, Jacques Esteve,
Ikuko Kato, and Rudolf Kaaks for useful discussions and recommendations
concerning this topic. We are indebted to all study participants; to the gynecol-ogists, pathologists, and oncologists who facilitated the identification of the
participants; and to the supervisors of the field work.
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