Abstract
Purpose In many diseases, it is possible to classify a heterogeneous group into subgroups relative to tumor biology, genetic
variations, or clinical and pathological features. No such classification is available for endometriosis. In our retrospective
case–case analysis we defined subgroups of endometriosis patients relative to the type and location of the endometriosis
lesion and relative to basic patient characteristics.
Methods
From June 2013 to July 2017, a total of 1576 patients with endometriosis diagnosed at surgery were included in
this study. The patients’ history and clinical data were documented using a web-based remote data entry system. To build
subgroups, all possible combinations of endometriosis locations/types (peritoneal; ovarian endometriosis; deeply infiltrat-
ing endometriosis; adenomyosis) were used. Due to the variation in group sizes, they were combined into five substantial
larger groups.
Results
Age, pregnancy rate, and live birth rate were identified as characteristics that significantly differed between the five
patient groups that were defined. No significant differences were noted in relation to body mass index, length of menstrual
cycle, age at menarche, reason for presentation, or educational level.
Conclusion
This study describes basic patient characteristics in relation to common clinical subgroups in a large clinical
cohort of endometriosis patients. Epidemiological information about different clinical groups may be helpful in identifying
groups with specific clinical courses, potentially suggesting novel approaches to early detection and to surgical and systemic
treatment.
Keywords
Endometriosis · Case–case analysis · Classification
Introduction
Endometriosis is a disease that is heterogeneous in relation
to both symptoms and patterns of spread in the peritoneal
cavity. Patients usually present with lower abdominal pain
and dysmenorrhea and/or infertility, or may be asympto-
matic [1–3]. In the abdomen, endometriotic lesions can be
found either confined to the pelvis or spreading up to the
diaphragm [4, 5]. In some patients, endometriosis lesions are
not attached to the mesothelium superficially, but infiltrate
adjacent structures or organs [4].
For many diseases, classification has helped to improve
treatment, as it enables subgroups to be identified that have
different types of risk for the most important outcomes, or
different responses to specific therapies. In many diseases, it
is possible to classify a heterogeneous group into subgroups
relative to tumor biology, genetic variations, or clinical and
pathological features [ 6, 7]. This can make individualized
treatment possible, improving the disease-specific and over-
all survival for the patients. No such classification is avail-
able for endometriosis, although it is one of the most com-
mon diseases in women of reproductive age and reduces
their quality of life and ability to work [8].
* Alexander Hein
[email protected]
1 Department of Gynecology and Obstetrics, University
Endometriosis Center for Franconia, Erlangen University
Hospital, Friedrich Alexander University of Erlangen-
Nuremberg, Universitätsstrasse 21–23, 91054 Erlangen,
Germany
978 Archives of Gynecology and Obstetrics (2022) 305:977–984
1 3
There are only descriptive endometriosis classifications,
but they do not classify a heterogenous group into subgroups
relative to clinically relevant features. The most common are
specific classification systems, such as the revised Ameri-
can Society for Reproductive Medicine (rASRM) score [9 ]
and the Enzian classification [10]. The latter classification
system describes different locations for deeply infiltrating
endometriotic lesions in general. The rASRM score is a
weighted scoring system for assessing endometrial implants,
plaques, endometriomas, and/or adhesions on the ovaries
and/or peritoneum. None of the available classification sys-
tems gathers together all the different types of endometriotic
lesion [11]. It is not possible to derive subgroups from any of
these classifications that would be of meaningful diagnostic
or therapeutic relevance.
Some studies have investigated the relationship between
patient characteristics and endometriosis [12], but no
attempts have previously been made to correlate patient
characteristics such as age at diagnosis, body mass index
(BMI), length of menstrual cycle, age at menarche, reason
for consultation, pregnancy rates, live birth rates, or educa-
tional level with subgroups of endometriosis patients. Some
of these patient characteristics have been recognized as rep-
resenting risk factors for endometriosis in general [13, 14].
The aim of this study was therefore to identify groups of
patients with endometriosis and to investigate the character-
istics of patients in different groups. This may be helpful for
further specifying and individualizing endometriosis therapy
[15], whether surgical and/or medical, and thus improving
the patients’ quality of life.
Methods
Study population
This retrospective observational study was conducted from
June 2013 to July 2017 in the Department of Gynecol-
ogy and Obstetrics at Erlangen University Hospital. It was
designed as a case–case analysis in which different groups
of patients with the same disease were compared with each
other. Patients who were diagnosed with endometriosis at
laparoscopy during this time span were eligible for inclu-
sion. The time of the patient’s first operation in Erlangen
University Hospital during this period was defined as the
time of first presentation. A total of 1576 patients in whom
endometriosis was diagnosed at surgery were identified. The
diagnosis date was the earliest date on which endometriosis
was first diagnosed at surgery. Of the 1576 patients, 356 had
missing data or an imprecise surgical diagnosis and were
excluded. A further 144 patients were excluded because
information about the type and location of the endometrio-
sis was missing. After all the exclusion criteria had been
applied, the remaining study population was 1076 patients
(Supplementary Fig. 1). All of the participants provided
written informed consent and the medical faculty’s ethics
committee approved the study.
Data acquisition
The data collected was obtained from the patients’ charts or
from a structured questionnaire completed by patients. The
patients’ history and clinical data were documented using a
web-based remote data entry system (electronic case report
form, eCRF) [15] and were transferred to an MS Access
database for further variable extraction. The eCRF collects
data on 23 variables at registration, and data on at least 41
variables were collected when the patient’s medical history
was being documented. In addition, at least 22 endometrio-
sis-specific variables were recorded; if the patient underwent
surgery for endometriosis, data on a further 18 variables
were recorded. Detailed information was collected regard-
ing age at first diagnosis, body mass index, age at menarche,
menstrual cycle length, number of pregnancies and live
births, educational level, marital status, ethnicity and current
employment, diseases apart from endometriosis, reason for
consultation, the way in which endometriosis was diagnosed,
detailed surgical information, grade and location of endo-
metriosis, and histological information. The basic patient
characteristics are listed in Table 1. This procedure allows
the type of endometriosis diagnosis to be differentiated very
precisely, with the data showing whether the patient had
superficial endometriosis, deeply infiltrating endometriosis
(DIE), endometrioma, and/or adenomyosis uteri.
Definition of groups
Endometriosis was diagnosed during laparoscopic sur -
gery in 1076 patients. Preoperative a standardized vaginal
examination and ultrasound was performed. Endometrio-
sis was diagnosed through histological examination of the
specimens. In cases where a histologic diagnosis was not
available, the diagnosis and determination of the spread of
endometriosis, e.g., adenomyosis, was made by the surgeon
based on the preoperative and perioperative findings. The
earliest date of an operation during which endometriosis was
diagnosed in each patient was used as the date of diagnosis.
Since no clinically relevant subgroups can be defined with
the available classifications, we decided to define the sub-
groups based on the type and location of the endometriosis.
In addition, the available classifications are too specific and
do not cover all types of endometriotic lesions. To build
subgroups without presuppositions, all possible combina-
tions of endometriosis locations (peritoneal, yes/no; ovarian
endometriosis, yes/no; deeply infiltrating endometriosis, yes/
no; adenomyosis, yes/no) were used On the basis of these
979Archives of Gynecology and Obstetrics (2022) 305:977–984
1 3
four criteria, which could either be present or not, 16 distinct
groups were formed. Each patient could be assigned to a
specific group. However, one group—with no endometrio-
sis and with all four criteria negative (subgroup 16)—did
not exist (Supplementary Table 1). The 1076 patients were
clearly allocated to one of the 15 subgroups. The subgroups
had widely varying sizes, ranging from two to 350 patients.
Due to the variation in group sizes, it was not practicable to
investigate all 15 subgroups and they were therefore com-
bined into meaningful larger groups: 1—peritoneal endome-
triosis only; 2—peritoneal endometriosis and adenomyosis;
3—adenomyosis only; 4—peritoneal and DIE-dominant;
and 5—endometrioma-dominant and other findings (Table 2
and Supplementary Fig. 2 [ 16]). It may be hypothesized that
these different types need different treatment approaches.
Further research will be needed to validate these results and
attempt to identify predictive factors to assist in the choice
of therapy.
Statistical considerations
The patients’ characteristics are presented as means with
standard deviation, or counts and percentages.
One-way analysis of variation (ANOVA) was performed
for the characteristics of age at first diagnosis of endometrio-
sis, BMI, age at menarche, and length of menstrual cycle.
For categorical variables such as the number of pregnan-
cies, number of live births, educational level, and main
reason for presentation, a Chi-squared test was performed.
Three categories were formed to examine pregnancy rates:
patients without pregnancies, patients with one pregnancy,
and patients with two or more pregnancies. The same pro-
cedure was used for live birth rates. Educational level was
divided into two groups: patients with a university degree
and patients without a university degree. The main reason
for consultation was classified into pain, infertility, or other
reasons.
All of the tests were two-sided, and a P value < 0.05 was
regarded as statistically significant. Calculations were car -
ried out using the R system for statistical computing (version
2.13.1; R Development Core Team, Vienna, Austria, 2011).
Results
The average age at which endometriosis was first diagnosed
was 33.9 years (SD ± 8.4). The study population was eth-
nically very homogeneous. Most of the patients were of
European ethnicity (93.2%); only 5.4% were Asian, and the
remainder (1.4%) were of other backgrounds. In all, 36.9%
of the patients had a university degree. The patients’ mean
BMI was in the upper normal range, at 24.1 (SD ± 5.1).
The mean length of the menstrual cycle was 28.5 days
(SD ± 9.0). The mean age at menarche was 13.0 years. The
patients’ main reasons for consultation were pain (48.5%),
followed by infertility (27.5%), and 24% had other rea-
sons for consultation. A total of 944 of the 1076 patients
(87.7%) underwent their first operation during this study;
Table 1 Patient characteristics
The table shows the patient characteristics oft the study population
BMI body mass index
Patient characteristics Mean or
frequency
Standard
deviation or
percent
Total 1076 100%
Age at first diagnosis (y) 33.9 ± 8.4
BMI at first presentation (kg/m2) 24.1 ± 5.1
Age at menarche (y) 13.0 ± 1.5
Length of menstrual cycle (days) 28.6 ± 9.0
Number of pregnancies at first presentation
0 670 62.7%
1 190 17.8%
≥ 2 209 19.6%
Number of live births
0 769 72.1%
1 144 13.5%
≥ 2 154 14.4%
Educational level
University 142 36.9%
Other 243 63.1%
Ethnicity
European 138 93.2%
Hispanic American 0 –
African 0 –
Asian 8 5.4%
Other 2 1.4%
Current employment
Employed full-time/part-time 82 59.4%
Retired 3 2.2%
Housewife 20 14.5%
Student 28 20.3%
Unemployed 5 3.6%
Main reason for presentation
Pain 520 48.5%
Infertility 295 27.5%
Other 258 24.0%
Previous surgery
0 944 87.7%
1 112 10.4%
≥ 2 20 1.9%
Medical history
No previous therapy 952 88.5%
Previous therapy 98 9.1%
980 Archives of Gynecology and Obstetrics (2022) 305:977–984
1 3
112 patients (10.4%) had had one previous operation, and
20 patients (1.9%) had had more than one previous opera -
tion. Most of the patients (n = 952, 88.5%) had not had any
previous therapy. Ninety-eight patients (9.1%) had already
received drug therapy. Only 79 of them were using hormo-
nal therapy such as contraceptives, a hormonal intrauterine
device (IUD) or gonadotropin-releasing hormone (GnRH)
agonists. No information about previous therapy was avail-
able for 26 patients (2.4%) (Table 1).
Peritoneal endometriosis was found in 82.8% of the 1076
patients. Diagnoses of adenomyosis uteri were less common,
at 37.5%, followed by deeply infiltrating endometriosis at
27.8% and endometrioma at 27.0%.
Adenomyosis was diagnosed in 404 patients. Most often,
adenomyosis was diagnosed intraoperatively. Only 76
patients had a histology of adenomyosis after hysterectomy.
The 76 patients with histologically confirmed adenomyosis
were almost evenly distributed among the different groups.
In the group “Adenomyosis only” were 25 of 115 patients
and in the group “Peritoneal endometriosis and adenomyo-
sis” 22 of 142 patients with histologically confirmed adeno-
myosis. The remaining patients were distributed among the
other groups. A correlation between histologically diagnosed
adenomyosis and older age is possible, but due to the even
distribution of the histologically confirmed adenomyosis, it
is rather unlikely.
The data showed that the mean age at the first diagno-
sis of endometriosis differed significantly in the different
groups (P < 0.001). Patients with peritoneal endometriosis
only (group 1) were more than 3 years younger (32.5 years)
than patients with adenomyosis uteri (35.9 years) (Table 3;
Supplementary Fig. 3). In comparison with the other groups,
the group with adenomyosis only had the lowest rate without
pregnancy (42.5%) and the lowest rate without a live birth
(53.6%). Over 30.4% of patients with adenomyosis had at
least two live births, while 16.1% had one live birth. This
Table 2 Division of the subgroups into five patient groups
All the 15 subgroups were combined into meaningful larger groups
DIE deeply infiltrating endometriosis
Endometriosis location in subgroups n (%) in subgroup Group n (%) in group
Peritoneal yes/endometrioma no /DIE no/adenomyo-
sis no
350 (32.5) Group 1: Peritoneal endometriosis only 350 (32.5)
Peritoneal yes/endometrioma no / DIE no/adenomyo-
sis yes
142 (13.2) Group 2: Peritoneal endometriosis and adenomyosis 142 (13.2)
Peritoneal no/endometrioma no /DIE no/adenomyosis
yes
115 (10.7) Group 3: Adenomyosis 115 (10.7)
Peritoneal yes/endometrioma no /DIE yes/adenomyo-
sis no
105 (9.8) Group 4: Peritoneal and DIE-dominant 275 (25.6)
Peritoneal yes/endometrioma yes/DIE yes/adenomyo-
sis no
60 (5.6)
Peritoneal yes/endometrioma no /DIE yes/adenomyo-
sis yes
57 (5.3)
Peritoneal yes/endometrioma yes/DIE yes/adenomyo-
sis yes
53 (4.9)
Peritoneal yes/endometrioma yes/DIE no/adenomyo-
sis no
99 (9.2) Group 5: Endometrioma-dominant and other 194 (18.0)
Peritoneal no/endometrioma yes /DIE no/adenomyo-
sis no
40 (3.7)
Peritoneal yes/endometrioma yes/DIE no/adenomyo-
sis yes
25 (2.3)
Peritoneal no/endometrioma no /DIE yes/adenomyo-
sis no
14 (1.3)
Peritoneal no/endometrioma yes /DIE no/adenomyo-
sis yes
6 (0.6)
Peritoneal no/endometrioma yes /DIE yes/adenomyo-
sis no
4 (0.4)
Peritoneal no/endometrioma yes /DIE yes/adenomyo-
sis yes
4 (0.4)
Peritoneal no/endometrioma no /DIE yes/adenomyo-
sis yes
2 (0.2)
Total 1076 (100.0) All groups 1076 (100.0)
981Archives of Gynecology and Obstetrics (2022) 305:977–984
1 3
Table 3 Patient characteristics in the five patient groups
The table shows the patient characteristics per group. In our study we tested for differences between the five groups. The mean age at first diag-
nosis of endometriosis differed significantly in the different groups (P < 0.001). There were also significant results for pregnancies (P < 0.001)
and for live births (P < 0.001). There were no significant differences between the other patient characteristics
BMI body mass index, DIE deeply infiltrating endometriosis
Group 1
Peritoneal only
n = 350 (32.5%)
Mean (SD) or n (%)
Group 2
Peritoneal &
adenomyosis
n = 142
(13.2%)
Mean (SD)
or n (%)
Group 3
Adenomyosis only
n = 115 (10.7%)
Mean (SD) or n (%)
Group 4
Peritoneal & DIE
n = 275 (25.6%)
Mean (SD) or n (%)
Group 5
Endometrioma
n = 194 (18.0%)
Mean (SD) or n (%)
Total
n = 1076 (100%)
Mean (SD) or n (%)
Age at first diagno-
sis (y)
32.6 (9.1)
n = 350
33.3 (8.1)
n = 142
35.9 (9.9)
n = 115
34.3 (7.2)
n = 275
35.0 (7.5)
n = 194
33.9 (8.4)
n = 1076
BMI at first presen-
tation (kg/m2)
24.0 (5.5)
n = 279
24.5 (5.1)
n = 90
24.3 (4.7)
n = 74
24.0 (5.2)
n = 211
24.2 (4.7)
n = 159
24.1 (5.1)
n = 813
Age at menarche (y) 13.0 (1.4)
n = 318
13.0 (1.7)
n = 137
12.8 (1.6)
n = 106
13.1 (1.4)
n = 255
13.0 (1.5)
n = 175
13.0 (1.5)
n = 991
Length of menstrual
cycle (days)
28.1 (5.2)
n = 183
29.1 (8.5)
n = 80
30.4 (14.2)
n = 58
27.7 (3.3)
n = 168
29.4 (15.0)
n = 111
28.6 (9.0)
n = 600
No. of pregnancies at first presentation
0 229 (66.2) 82 (58.2) 48 (42.5) 186 (67.6) 125 (64.4) 670 (62.7)
1 55 (15.9) 34 (24.1) 20 (17.7) 51 (18.5) 30 (15.5) 190 (17.8)
≥ 2 62 (17.9) 25 (17.7) 45 (39.8) 38 (13.8) 39 (20.1) 209 (19.6)
Total 346 (100) 141 (100) 113 (100) 275 (100) 194 (100) 1069 (100)
No. of live births
0 259 (75.1) 102 (72.3) 60 (53.6) 211 (76.7) 137 (70.6) 769 (72.1)
1 44 (12.8) 18 (12.8) 18 (16.1) 36 (13.1) 28 (14.4) 144 (13.5)
≥ 2 42 (12.2) 21 (14.9) 34 (30.4) 28 (10.2) 29 (14.9) 154 (14.4)
Total 345 (100) 141 (100) 112 (100) 275 (100) 194 (100) 1067 (100)
Educational level
University 52 (39.4) 15 (34.1) 8 (26.7) 42 (40.4) 25 (33.3) 142 (36.9)
Other 80 (60.6) 29 (65.9) 22 (73.3) 62 (59.6) 50 (66.6) 243 (63.1)
Total 132 (100) 44 (100) 30 (100) 104 (100) 75 (100) 385 (100)
Ethnicity
European 43 (91.5) 16 (94.1) 8 (88.9) 44 (95.7) 27 (93.1) 138 (93.2)
Hispanic Ameri-
can
0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0)
African 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0)
Asian 3 (6.4) 1 (5.9) 0 (0.0) 2 (4.3) 2 (6.9) 8 (5.4)
Other 1 (2.1) 0 (0.0) 1 (11.1) 0 (0.0) 0 (0.0) 2 (1.4)
Total 47 (100) 17 (100) 9 (100) 46 (100) 29 (100) 148 (100)
Current employment
Employed full-
time/part-time
22 (50.0) 10 (71.4) 7 (50.0) 27 (71.1) 16 (57.1) 82 (59.4)
Retired 2 (4.5) 0 (0.0) 0 (0.0) 0 (0.0) 1 (3.6) 3 (2.2)
Housewife 6 (13.6) 1 (7.1) 4 (28.6) 3 (7.9) 6 (21.4) 20 (14.5)
Student 13 (29.5) 3 (21.4) 2 (14.3) 7 (18.4) 3 (10.7) 28 (20.3)
Unemployed 1 (2.3) 0 (0.0) 1 (7.1) 1 (2.6) 2 (7.1) 5 (3.6)
Total 44 (100) 14 (100) 14 (100) 38 (100) 28 (100) 138 (100)
Main reason for presentation
Pain 166 (47.7) 73 (51.4) 67 (58.3) 129 (46.9) 85 (44.0) 520 (48.5)
Infertility 87 (25.0) 45 (31.7) 24 (20.9) 85 (30.9) 54 (28.0) 295 (27.5)
Other 95 (27.3) 24 (16.9) 24 (20.9) 61 (22.2) 54 (28.0) 258 (24.0)
Total 348 (100) 142 (100) 115 (100) 275 (100) 193 (100) 1073 (100)
982 Archives of Gynecology and Obstetrics (2022) 305:977–984
1 3
means that 46.5% of the patients with adenomyosis had
at least one child, in comparison with the other groups, in
which fewer than 30% had at least one live birth (Supple-
mentary Figs. 4 and 5). There were also significant results
for pregnancies (P < 0.001) and for live births (P < 0.001)
(Table 3). In view of the high rates of pregnancy and live
births, infertility as the main reason for consultation was
rare in the group with adenomyosis. However, there were
no significant differences between the five groups in rela-
tion to this parameter (P = 0.62). There were also no sig-
nificant differences between the groups in relation to body
mass index, educational level, length of menstrual cycle, or
age at menarche.
Discussion
In this retrospective case–case study, basic patient charac-
teristics were associated with the location of endometrio-
sis by developing subgroups of endometriosis lesions. In
five defined groups, significant differences were found in
the patient’s mean ages at first diagnosis of endometriosis.
Significant differences were also found between pregnancy
rates and also between live birth rates in the groups.
It has been shown in previous studies that there is a risk
of developing endometriosis only during women’s repro-
ductive years. In earlier studies, the highest risk was found
to be at 44 years of age [17], with another peak between 25
and 29 years. The highest risk reported in recent studies was
between 25 and 29 years. The risk was found to decrease
after the age of 44 in all of the studies [12, 18, 19]. In the
present study, the mean age at onset was 33.9 years. There is
a known delay between the first symptoms and the diagnosis
of endometriosis at surgery. In addition, the time of the first
operation is influenced by socio–economic factors such as
education, access to special medical facilities, or age at the
onset of symptoms [8 , 20, 21]. This can delay the surgical
diagnosis of endometriosis. However, as the present study
involved a case–case analysis, the mean age may be influ-
enced, but not the differences between the groups.
There have only been a few studies examining endo-
metriosis groups. In one study, no significant difference
was found between patients with DIE and patients with
peritoneal endometriosis or endometrioma [22]. In another
study, a significant difference was found between the
average age of women diagnosed with endometriosis and
women diagnosed with adenomyosis uteri. Patients with
endometriosis were younger than those with adenomyosis
uteri [23]. The present study examined whether there were
any differences between five defined groups. The mean age
at first diagnosis of endometriosis differed significantly in
the group analysis. Patients with adenomyosis uteri were
3 years older than patients with peritoneal endometriosis
only. In the present study, there were two diagnostic meth-
ods of identifying adenomyosis uteri—either through his-
tology or the surgeon’s impression. However, hysterec-
tomy was avoided in young patients, and this may have
influenced the high mean age in patients with adenomyosis
uteri. Nevertheless, the mean age in the group with perito-
neal endometriosis and adenomyosis uteri was the second
lowest in all the groups. It is not therefore expected that
the results may have been biased as a result of the diag-
nostic methods used.
The data showed significant differences between the
groups in relation to pregnancy rates and also live birth
rates, and suggest that patients with adenomyosis have a
higher pregnancy rate and live birth rate than patients in
the other four groups. In previous studies, adenomyosis in
particular is considered to be a cause of infertility and mis-
carriage when assisted reproductive techniques are used [24,
25]. Other studies have primarily examined the influence of
endometriosis on infertility [26]. However, there are no data
on the pregnancy rate and live birth rate with spontaneous
conception. In addition, no studies were found in the litera-
ture that have compared pregnancy rates or live birth rates
between different groups with endometriosis. The average
rates for women without pregnancy and without live births
were high. However, comparison with a control group was
not available and it is therefore not possible to draw any con-
clusions regarding infertility in comparison with a healthy
population.
The odds of developing endometriosis have been reported
to be lower among women with histologically confirmed
endometriosis who had a large versus lean body size [27];
a higher body mass index may also be associated with a
lower risk of endometriosis [28]. In a subgroup analysis,
obese women were found to be more likely to have a surgi-
cal diagnosis of adenomyosis [23]. In the present study, the
groups with adenomyosis uteri had the highest BMI, but the
differences were not significant.
With regard to the menstrual cycle, current studies
assume that frequent menstrual bleeding is a risk factor for
endometriosis. Early age at menarche, shorter menstrual
cycles and thus more frequent period bleeding, longer bleed-
ing periods, and few pregnancies appear to be risk factors
[29]. It has previously been reported that age at menarche
did not differ between patients who underwent hysterectomy
with a diagnosis of adenomyosis and those who did not have
a diagnosis of adenomyosis [30].
There is not known to be any association between endo-
metriosis and educational level [8], but no subgroup analyses
have as yet been published.
No differences were found between the groups with
regard to the main reasons for consultation. These data are
consistent with data showing that there is no association
between the extent of endometriosis and pain [31]. On the
983Archives of Gynecology and Obstetrics (2022) 305:977–984
1 3
other hand, there is some evidence that adenomyosis uteri
is associated with pain [32].
Case selection in a hospital-based study may be biased by
the variety of health care that is provided in the hospital con-
cerned. Women seeking help for pelvic pain might increase
the numbers of cases of pain-inducing endometriosis, and
a hospital providing specialized health care for infertility
patients might have larger numbers of patients. In the pre-
sent study, the hospital is a center for all types of treatment,
so that a bias toward one of these groups seems unlikely.
Patients who underwent surgical therapy were selected. The
study group included therefore does not correspond to the
normal distribution of endometriosis patients and thus does
not represent an adequate epidemiological picture.
One major limitation of the study is that pregnancy rates
and live birth rates may be influenced by other patient char-
acteristics, such as the main reason for consultation or mean
age. The present data are only able to show associations, but
not causality.
Another limitation is the type of diagnostic method used
to identify adenomyosis uteri through clinical aspects and
the surgeon’s impression. The diagnosis of adenomyosis
uteri is clinically challenging, as there is no consensus on
the best imaging features for a nonsurgical diagnosis of
adenomyosis [33]. Nevertheless, standardized preoperative
ultrasound was performed in our study in 1045 of the 1076
cases. Adenomyosis was suspected in 135 patients. All of
the patients underwent a preoperative vaginal examination.
The gold standard of hysterectomy cannot be applied in this
population. In relation to international guidelines, it was
decided that the surgeon should make the intraoperative
diagnosis of an endometriosis on the basis of the medical
history and preoperative clinical findings [34]. Histological
diagnosis of the disease or longer-term follow-up data might
be helpful for refining the groups.
In conclusion, this study has added to the evidence that
different subgroups exist among endometriosis patients. It
may be hypothesized that these different types need differ -
ent treatment approaches. Further research will be needed
to confirm these results and attempt to identify predictive
factors to assist in the choice of therapy,
Supplementary Information The online version contains supplemen-
tary material available at https:// doi. org/ 10. 1007/ s00404- 021- 06200-w.
Acknowledgements
The contribution of Simon Blum to this publica-
tion was performed in partial fulfillment of the requirements for obtain-
ing the degree of Doctor of Medicine. Parts of the research published
here have been used for his doctoral thesis at the Medical Faculty of
Friedrich Alexander University of Erlangen–Nuremberg (FAU).
Author contributions SB: protocol/project development, data col-
lection or management, data analysis, manuscript writing/editing.
PAF: protocol/project development, data collection or management,
data analysis, manuscript writing/editing. TH: manuscript editing.
JL: manuscript editing. FH: manuscript editing. TB: manuscript edit-
ing. HL: manuscript editing. SA: manuscript editing. KB: manuscript
editing. CF: manuscript editing. KH: manuscript editing. SB: proto-
col/project development, manuscript writing/editing. MWB: project
development, manuscript editing. AH: protocol/project development,
manuscript writing/editing.
Funding Open Access funding enabled and organized by Projekt
DEAL.
Declarations
Conflicts of interest There were no conflicts of interest.
Ethics approval The medical faculty’s ethics committee approved the
study.
Open Access This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long
as you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article are
included in the article’s Creative Commons licence, unless indicated
otherwise in a credit line to the material. If material is not included in
the article’s Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will
need to obtain permission directly from the copyright holder. To view a
copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
References
1. Fauconnier A, Chapron C (2005) Endometriosis and pelvic pain:
epidemiological evidence of the relationship and implications.
Hum Reprod Update 11(6):595–606
2. Schliep KC et al (2015) Pain typology and incident endometriosis.
Hum Reprod 30(10):2427–2438
3. Burghaus S et al (2019) Standards used by a clinical and scientific
endometriosis center for the diagnosis and therapy of patients with
endometriosis. Geburtshilfe Frauenheilkd 79(5):487–497
4. Nisolle M, Donnez J (1997) Peritoneal endometriosis, ovarian
endometriosis, and adenomyotic nodules of the rectovaginal sep-
tum are three different entities. Fertil Steril 68(4):585–596
5. Audebert A et al (2018) Anatomic distribution of endometriosis: a
reappraisal based on series of 1101 patients. Eur J Obstet Gynecol
Reprod Biol 230:36–40
6. Curtis C et al (2012) The genomic and transcriptomic architec-
ture of 2,000 breast tumours reveals novel subgroups. Nature
486(7403):346–352
7. Prat J (2012) Ovarian carcinomas: five distinct diseases with dif-
ferent origins, genetic alterations, and clinicopathological fea-
tures. Virchows Arch 460(3):237–249
8. Nnoaham KE et al (2011) Impact of endometriosis on quality of
life and work productivity: a multicenter study across ten coun-
tries. Fertil Steril 96(2):366-373.e8
9. American Society for Reproductive Medicine (1997) Revised
American Society for Reproductive Medicine classification of
endometriosis: 1996. Fertil Steril 67(5):817–821
10. Haas D et al (2013) The rASRM score and the Enzian classifi-
cation for endometriosis: their strengths and weaknesses. Acta
Obstet Gynecol Scand 92(1):3–7
984 Archives of Gynecology and Obstetrics (2022) 305:977–984
1 3
11. Johnson NP et al (2017) World Endometriosis Society con-
sensus on the classification of endometriosis. Hum Reprod
32(2):315–324
12. Missmer SA et al (2004) Incidence of laparoscopically confirmed
endometriosis by demographic, anthropometric, and lifestyle fac-
tors. Am J Epidemiol 160(8):784–796
13. Burghaus S et al (2011) Risk factors for endometriosis in a german
case-control study. Geburtsh Frauenheilk 71(12):1073–1079
14. Shah DK et al (2013) Body size and endometriosis: results from
20 years of follow-up within the Nurses’ Health Study II prospec-
tive cohort. Hum Reprod 28(7):1783–1792
15. Burghaus S et al (2016) The international endometriosis evalu-
ation program (IEEP Study)—a systematic study for physicians
researchers and patients. Geburtsh Frauenheilk 76(8):875–881
16. Hulsen T, de Vlieg J, Alkema W (2008) BioVenn, a web applica-
tion for the comparison and visualization of biological lists using
area-proportional Venn diagrams. BMC Genom 9:488
17. Velebil P et al (1995) Rate of hospitalization for gynecologic
disorders among reproductive-age women in the United States.
Obstet Gynecol 86(5):764–769
18. Houston DE et al (1988) The epidemiology of pelvic endometrio-
sis. Clin Obstet Gynecol 31(4):787–800
19. Sangi-Haghpeykar H, Poindexter AN 3rd (1995) Epidemiol-
ogy of endometriosis among parous women. Obstet Gynecol
85(6):983–992
20. Staal AH, van der Zanden M, Nap AW (2016) Diagnostic Delay
of Endometriosis in the Netherlands. Gynecol Obstet Invest
81(4):321–324
21. Soliman AM, Fuldeore M, Snabes MC (2017) Factors associ -
ated with time to endometriosis diagnosis in the United States. J
Womens Health (Larchmt) 26(7):788–797
22. Parazzini F et al (2008) Risk factors for deep endometriosis: a
comparison with pelvic and ovarian endometriosis. Fertil Steril
90(1):174–179
23. Templeman C et al (2008) Adenomyosis and endometriosis in the
California Teachers Study. Fertil Steril 90(2):415–424
24. Maheshwari A et al (2012) Adenomyosis and subfertility: a sys-
tematic review of prevalence, diagnosis, treatment and fertility
outcomes. Hum Reprod Update 18(4):374–392
25. Vercellini P et al (2014) Uterine adenomyosis and in vitro ferti-
lization outcome: a systematic review and meta-analysis. Hum
Reprod 29(5):964–977
26. Harb HM et al (2013) The effect of endometriosis on in vitro fer -
tilisation outcome: a systematic review and meta-analysis. BJOG
120(11):1308–1320
27. Farland LV et al (2017) Associations among body size across
the life course, adult height and endometriosis. Hum Reprod
32(8):1732–1742
28. Liu Y, Zhang W (2017) Association between body mass
index and endometriosis risk: a meta-analysis. Oncotarget
8(29):46928–46936
29. Saha R, Marions L, Tornvall P (2017) Validity of self-reported
endometriosis and endometriosis-related questions in a Swedish
female twin cohort. Fertil Steril 107(1):174-178.e2
30. Vercellini P et al (1995) Adenomyosis at hysterectomy—a study
on frequency-distribution and patient characteristics. Hum Reprod
10(5):1160–1162
31. Koninckx PR et al (1991) Suggestive evidence that pelvic endo-
metriosis is a progressive disease, whereas deeply infiltrat-
ing endometriosis is associated with pelvic pain. Fertil Steril
55(4):759–765
32. Perello MF et al (2017) Endometriotic pain is associated with
adenomyosis but not with the compartments affected by deep
infiltrating endometriosis. Gynecol Obstet Invest 82(3):240–246
33. Andres MP et al (2018) Transvaginal ultrasound for the diagnosis
of adenomyosis: systematic review and meta-analysis. J Minim
Invasive Gynecol 25(2):257–264
34. Dunselman GA et al (2014) ESHRE guideline: management of
women with endometriosis. Hum Reprod 29(3):400–412
Publisher's Note Springer Nature remains neutral with regard to
jurisdictional claims in published maps and institutional affiliations.
Text is read by the "Ask this paper" AI Q&A widget below.
Extraction quality varies by source — PMC NXML preserves structure
cleanly, OA-HTML may include some navigation residue, and OA-PDF can
have broken hyphenation. The publisher copy
(via DOI)
is the canonical version.