American Journal of Epidemiology © The Author 2016. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: [email protected].
Vol. 184, No. 9 DOI: 10.1093/aje/kww086 Advance Access publication: October 13, 2016
Practice of Epidemiology Estimating the Prevalence of Ovarian Cancer Symptoms in Women Aged 50 Years or Older: Problems and Possibilities
Zhuoyu Sun*, Lucy Gilbert, Antonio Ciampi, Jay S. Kaufman, and Olga Basso * Correspondence to Zhuoyu Sun, Department of Epidemiology, Biostatistics and Occupational Health, Faculty of Medicine, McGill University, 1020 Pine Avenue West, Montreal, Quebec H3A 1A2, Canada (e-mail: [email protected]).
Initially submitted December 3, 2015; accepted for publication February 2, 2016.
Diagnostic testing is recommended in women with “ovarian cancer symptoms.” However, these symptoms are nonspecific. The ongoing Diagnosing Ovarian Cancer Early (DOVE) Study in Montreal, Quebec, Canada, provides diagnostic testing to women aged 50 years or older with symptoms lasting for more than 2 weeks and less than 1 year. The prevalence of ovarian cancer in DOVE is 10 times that of large screening trials, prompting us to estimate the prevalence of these symptoms in this population. We sent a questionnaire to 3,000 randomly sampled women in 2014–2015. Overall, 833 women responded; 81.5% reported at least 1 symptom, and 59.7% reported at least 1 symptom within the duration window specified in DOVE. We explored whether such high prevalence resulted from low survey response by applying inverse probability weighting to correct the estimates. Older women and those from deprived areas were less likely to respond, but only age was associated with symptom reporting. Prevalence was similar in early and late responders. Inverse probability weighting had a minimal impact on estimates, suggesting little evidence of nonresponse bias. This is the first study investigating symptoms that have proven to identify a subset of women with a high prevalence of ovarian cancer. However, the high frequency of symptoms warrants further refinements before symptom-triggered diagnostic testing can be implemented. mail survey; nonresponse; nonresponse bias; ovarian cancer symptoms; prevalence
Abbreviations: DOVE, Diagnosing Ovarian Cancer Early; IPW, inverse probability weighting.
Although long considered a “silent killer,” ovarian cancer is often preceded by symptoms (1–7); this realization has led to the recommendation that women experiencing certain symptoms be tested to rule out ovarian cancer (8). However, the symptoms associated with ovarian cancer are common and nonspecific (3, 7, 9–11), and diagnostic tests for ovarian cancer have low sensitivity and specificity (12), which makes it unfeasible to investigate all symptomatic women (13). The ongoing Diagnosing Ovarian Cancer Early (DOVE) Study in Montreal, Quebec, Canada, has the objective of evaluating whether prompt assessment of symptomatic women aged 50 years or older results in earlier diagnosis of ovarian cancer and, ultimately, better prognosis (14). In the absence of rigorous prospective data, admission to DOVE was not determined by type, frequency, or
severity of symptoms. The only criterion imposed was that of duration, to avoid inclusion of transitory conditions on the one end and chronic conditions on the other. Thus, women were eligible for admission to DOVE if their symptoms had lasted more than 2 weeks and less than 1 year. The prevalence of invasive ovarian cancer in DOVE is about 10 times that observed at the first visit of large ovarian cancer screening trials (14). This finding prompted us to assess the prevalence of “ovarian cancer symptoms” in this population. We sent a questionnaire to a random sample of 3,000 women aged 50 years or older living in Montreal and up to 2 reminders to nonresponders. The crude response rate was 28%. Among eligible responders, 81.5% reported at least 1 symptom. The prevalence was reduced to 59.7% when restricted to the duration window specified in the
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Estimating Prevalence of Ovarian Cancer Symptoms 671
DOVE Study—still too high to trigger widespread diagnostic testing. On the other hand, this high prevalence may be due to the low response rate. Low response is a frequent problem in health surveys. Certain segments of the population, such as older individuals and those with lower socioeconomic status (13, 15), are particularly less likely to respond. If response is associated with having the condition(s) of interest, prevalence estimates can be severely affected by low response (16, 17). However, the response rate per se is a poor predictor of the magnitude of bias (18); more important is the extent to which nonresponse is associated with determinants of the outcome under study. For instance, in a survey with a response rate of 26%, Grievink et al. (19) did not find nonresponse to bias the estimated prevalence of the examined health conditions. In other studies, it was shown that increasing response rates by sending multiple mailings had little effect on prevalence (20, 21), but it increased bias due to reporting errors (22). However, the implications of low response have to be assessed on a case-by-case basis. Postsurvey adjustments (e.g., inverse probability weighting) are often applied to correct for nonresponse (23–26). In this study, we investigated the impact of nonresponse on the prevalence of “ovarian cancer symptoms” estimated from our survey and discuss the implications of diagnostic testing for ovarian cancer in symptomatic women. METHODS Questionnaire and study population
The questionnaire used in this survey was developed and pretested in an academic setting and included the symptoms determining eligibility for the DOVE Study (14). We pilot tested the questionnaire among 30 women aged 50 years or older who attended public presentations about DOVE, and we revised it based on poor completion and response time. The study population consisted of 3,000 women aged 50 years or older, living in the Greater Montreal area, randomly sampled among those covered by the Régie de l’Assurance Maladie du Québec (Quebec Health Insurance Plan), which covers virtually all Quebec residents. We obtained the names, preferred language, and addresses of the women and, in July 2014, we sent a mail package in French or English, containing a cover letter, the informed consent form, login details (for responders to reply online if they preferred), the questionnaire, and a prepaid return envelope. All responders were entered into a drawing to win a $100 gift card (one for every 200 participants who returned the questionnaire). Nonresponders were sent a reminder letter 7 weeks after the initial mailing and a second letter after a further 9 weeks. Women responding to the first, second, and third mailings were considered early, intermediate, and late responders, respectively. The study was approved by the institutional ethics review board of McGill University and the Commission d’Accès à l’Information du Québec. The questionnaire included questions about symptoms, sociodemographic characteristics (age, race/ethnicity, education, income, and marital and employment status), smoking status, and medical history (family history of cancer and Am J Epidemiol. 2016;184(9):670–680
cancer diagnosis), and responders were asked to rate their health status. The 31 symptoms were divided into 7 groups (see Web Appendix 1, available at http://aje.oxfordjournals. org/). Responders were asked to report the severity (from low to high on a scale of 1 to 5) and frequency of the symptom (all the time, daily, weekly, or monthly), as well as duration ( 0.2) (32). In the second step, using the IPW method, we reweighted survey responders up to the second sample of 3,000 to achieve representativeness with respect to health-care use (33). To avoid extreme weights, which can result in unstable estimates, we truncated weights below the first percentile and above the 99th percentile by setting them at the values of the first and 99th percentiles, respectively (34, 35). We then compared the preand postweighted data with the 2 random samples, with respect to sociodemographic factors (the entire eligible sample) and use of health-care services (the second sample, provided for this purpose). We used a robust, sandwich-type variance estimator to account for the fact that the weights were estimated (36). All analyses were carried out using SAS, version 9.3 (SAS Institute, Inc., Cary, North Carolina).
Table 1. Sociodemographic Characteristics of Responders and Nonresponders and Predictors of Nonresponse in a Mail Survey on Ovarian Cancer Symptoms Among Women Aged 50 Years or Older, Montreal, Quebec, Canada, 2014–2015 Characteristic
Responders (n = 771)
Nonresponders (n = 2,131)
No.
%a
%a
RRb
50–59
345
44.8
60–69
270
35.0
800
37.5
1.00
597
28.0
0.97
70–79
115
14.9
423
19.9
1.10
1.04, 1.17
41
5.3
311
14.6
1.22
1.16, 1.30
French
639
82.9
1713
80.4
1.00
0.74, 1.03
English
132
17.1
418
19.6
1.04
0.99, 1.10
Montreal Island
308
40.0
943
44.3
1.00
Suburbs
315
40.9
742
34.9
0.98
0.93, 1.03
Small towns and rural areas
147
19.1
444
20.9
1.01
0.95, 1.07
1 (least deprived)
207
26.9
421
19.8
1.00
2
171
22.2
394
18.5
1.06
1.00, 1.14
3
131
17.0
407
19.1
1.13
1.05, 1.21
4
127
16.5
380
17.9
1.13
1.05, 1.22
97
12.6
370
17.4
1.17
1.09, 1.25
1 (least deprived)
149
19.4
324
15.2
1.00
2
131
17.0
342
16.1
1.05
0.97, 1.14
3
135
17.5
363
17.1
1.04
0.96, 1.13
4
171
22.2
456
21.4
1.02
0.95, 1.10
5 (most deprived)
147
19.1
487
22.9
1.07
1.00, 1.16
Indices not assignedc
37
4.8
157
7.4
1.17
1.06, 1.30
No.
95% CI
Age, years
≥80
0.92, 1.03
Language
Place of residence
Material deprivation index
5 (most deprived) Social deprivation index
Abbreviations: CI, confidence interval; RR, relative risk. Values for some categories do not sum to 100% due to rounding. b RRs were adjusted for all other variables in the table. c This category includes, for the most part, geographic statistical areas with a high proportion of collective households or institutionalized persons. a
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RESULTS
We received 389 responses to the first wave of the survey, 303 to the second, and 141 to the third (with 25, 60, and 61 women, respectively, calling to decline participation at each wave). In total, 833 out of 3,000 women returned a
completed questionnaire (response rate = 28%). Only 7% answered online. Among responders, 62 (7.4%) reported a bilateral oophorectomy or a previous diagnosis of ovarian cancer, which made them ineligible for the study. There were 771 eligible responders. We also excluded from the total sample 36 of the 146 women who contacted us,
Table 2. Associations Between Sociodemographic Characteristics, Health-Care Use, and Reporting of at Least 1 Symptom (in the Defined Duration Windowa) Among Responders in a Mail Survey on Ovarian Cancer Symptoms Among Women Aged 50 Years or Older, Montreal, Quebec, Canada, 2014–2015
Characteristic
Responders With ≥1 Symptom (n = 628) No.
%b
RRc
50–59
288
83.5
1.00
60–69
222
82.2
70–79
89
≥80
Responders With ≥1 Symptom in Defined Duration Window (n = 460) %b
RRc
95% CI
No.
95% CI
209
60.6
1.00
1.00
0.93, 1.06
164
60.7
0.97
0.85, 1.10
77.4
0.92
0.83, 1.03
64
55.7
0.84
0.70, 1.00
29
70.7
0.82
0.68, 1.00
23
56.1
0.95
0.72, 1.25
French
523
81.9
1.00
English
105
79.6
0.99
Montreal Island
250
81.2
1.00
Suburbs
262
83.2
Small towns and rural areas
116
1 (least deprived) 2 3 4
Age, years
Language 381
59.6
1.00
0.90, 1.09
79
59.9
0.99
179
58.1
1.00
1.03
0.96, 1.10
196
62.2
1.08
0.95, 1.22
78.9
0.97
0.89, 1.05
85
57.8
1.03
0.87, 1.21
173
83.6
1.00
124
59.9
1.00
140
81.9
0.98
0.91, 1.06
104
60.8
1.02
0.87, 1.20
111
84.7
0.98
0.90, 1.08
82
62.6
1.06
0.90, 1.25
100
78.7
0.96
0.86, 1.06
78
61.4
1.05
0.89, 1.25
75
77.3
0.94
0.85, 1.04
52
53.6
0.91
0.74, 1.13
1 (least deprived)
126
84.6
1.00
90
60.4
1.00
2
108
82.4
0.97
0.88, 1.06
79
60.3
1.02
0.85, 1.23
3
113
83.7
0.99
0.90, 1.09
83
61.5
1.06
0.88, 1.27
4
140
81.9
0.97
0.88, 1.06
98
57.3
0.94
0.79, 1.13
5 (most deprived)
112
76.2
0.93
0.84, 1.03
90
61.2
1.05
0.88, 1.26
29
78.4
0.98
0.82, 1.17
20
54.1
0.94
0.68, 1.30
0.85, 1.15
Place of residence
Material deprivation index
5 (most deprived) Social deprivation index
d
Indices not assigned
Health-care utilization in the previous 5 yearse >30 general practitioner contacts
176
84.6
1.05
0.98, 1.13
135
64.9
1.12
1.00, 1.27
>35 specialist contacts
207
86.3
1.09
1.02, 1.16
162
67.5
1.20
1.07, 1.35
>1 hospitalization
170
83.3
1.01
0.94, 1.08
129
63.2
1.08
0.96, 1.23
59
78.7
0.91
0.80, 1.05
45
60.0
0.92
0.74, 1.15
>3 total hospital daysf
Abbreviations: CI, confidence interval; RR, relative risk. The duration window was defined as at least 2 weeks and less than 1 year, as specified in the Diagnosing Ovarian Cancer Early Study. b Percentage of women reporting symptoms in each row. c RRs were adjusted for all other variables in the table. d This category includes, for the most part, geographic statistical areas with a high proportion of collective households or institutionalized persons. e Cutoffs represent the averages of the use of health services in the Montreal population of women aged 50 years or older, calculated from the second random sample of 3,000. f Total number of hospital days is reported only among those with at least 1 hospitalization during the previous 5 years. a
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Table 3. Characteristics Among Subgroups of Responders in a Mail Survey on Ovarian Cancer Symptoms Among Women Aged 50 Years or Older, Montreal, Quebec, Canada, 2014–2015
Characteristic
Early Responders (n = 368)
Intermediate Responders (n = 274) %a
Late Responders (n = 129)
No.
%a
No.
50–59
164
44.6
126
46.0
55
42.6
60–69
134
36.4
86
31.4
50
38.8
70–79
57
15.5
41
15.0
17
13.2
≥80
13
3.5
21
7.7
7
5.4
355
96.7
248
90.8
114
88.4
12
3.3
25
9.2
15
11.6
French
306
83.2
225
82.1
108
83.7
English
62
16.9
49
17.9
21
16.3
Montreal Island
143
39.0
114
41.6
51
39.5
Suburbs
161
43.9
106
38.7
48
37.2
63
17.2
54
19.7
30
23.3
High school or less
128
34.9
115
42.0
55
42.6
College or technical school
102
27.8
68
24.8
32
24.8
University
137
37.3
91
33.2
42
32.6
No.
%a
Age, years
Race/ethnicityb White Nonwhite Language
Place of residence
Small towns and rural areas Educational level
Marital status Single
42
11.4
29
10.6
13
10.2
235
63.9
173
63.4
73
57.0
91
24.7
71
26.0
42
32.8
Employed
161
43.8
101
36.9
47
36.4
Retired
160
43.5
119
43.4
59
45.7
47
12.8
54
19.7
23
17.8 17.1
Married or common-law partner Separated, divorced, or widowed Employment status
Other Annual household income, Canadian dollarsb 30 general practitioner contacts
100
27.2
>35 specialist contacts
Intermediate Responders (n = 274) No.
%a
Late Responders (n = 129) No.
%a
d
Health-care utilization in the past 5 years
78
28.5
30
23.3
107
29.1
89
32.5
44
34.1
>1 hospitalization
93
25.3
76
27.7
35
27.1
>3 total hospital dayse
32
34.4
30
39.5
13
37.1
≥1 symptom
301
81.8
221
80.7
106
82.2
≥1 symptom within defined durationf
219
59.5
159
58.0
82
63.6
≥3 symptoms
242
65.8
173
63.1
89
69.0
≥1 frequent or severe symptom within defined durationg
146
39.7
112
40.9
63
48.8
Presence of symptoms
a
Values for some categories do not sum to 100% due to rounding. P < 0.05 for difference between early, intermediate, and late responders (χ2 tests). c This category refers to family history of ovarian, breast, and colon cancer. d Cutoffs represent the averages of the use of health services in the Montreal population of women aged 50 years or older, calculated from the second random sample of 3,000. e Total number of hospital days is reported only among those with at least 1 hospitalization during the previous 5 years. f The duration window was defined as at least 2 weeks and less than 1 year, as specified in the Diagnosing Ovarian Cancer Early Study. g This category refers to symptoms that are frequent or severe and that lasted for more than 2 weeks and less than 1 year. b
because they reported having had a “total” hysterectomy. After these exclusions, we had 2,902 eligible responders for analysis, although the true number of eligible responders (with at least 1 ovary and no prior diagnosis of ovarian cancer) would be lower. The average age of responders was 62 years (range, 50– 98 years). Response rates were significantly lower among women aged 70 years or older, women living in Montreal Island or rural areas, and women with higher material or social deprivation indices (Table 1). In multivariate analyses, only older age and living in more materially or socially deprived areas were significantly associated with nonresponse. In total, 81.5% of women reported at least 1 symptom, regardless of duration, and 59.7% reported 1 or more symptoms within the DOVE duration window. Younger age, but not deprivation index, was independently associated with reporting at least 1 symptom. Additionally, symptomatic women reported a higher use of health-care services in the previous 5 years (Table 2). Patterns were similar for reporting at least 1 symptom in the DOVE duration window (as well as for reporting ≥3 symptoms or ≥1 frequent or severe symptom in the DOVE duration window; see Web Table 1). When we tested the model without health-care use, results were unchanged. Compared with early responders, a higher proportion of intermediate and late responders were nonwhite, had an annual household income less than $50,000 (in Canadian dollars), and reported fair or poor health (as opposed to excellent or good health) (Table 3). There were no significant differences in health-care utilization between early and late responders. Prevalence of symptoms did not decline by wave of response. On the contrary, late responders more Am J Epidemiol. 2016;184(9):670–680
often reported having a frequent or severe symptom in the DOVE duration window. As shown in Table 4, before weighting, responders were more likely to be younger, living in the suburbs, and from more materially or socially privileged areas than the target population. In addition, responders had fewer than average contacts with their general practitioners and, if hospitalized in the past 5 years, spent fewer days in the hospital. After IPW adjustment, responders were more comparable to the target population with respect to sociodemographic factors and health-care use. The covariates retained in the final models are listed in Web Table 2. The overall prevalence of symptoms changed very little after weighting, either by sociodemographic factors or by sociodemographic factors and health-care utilization (Table 5; distribution of weights is shown in Web Figure 1). To check whether model selection affected the estimates, we repeated the analyses including all covariates and found no material difference (data not shown). The crude and weighted prevalence of the 6 most frequent symptoms differed considerably depending on whether or not they fell into the DOVE duration window (Figure 1).
DISCUSSION
In this study, the estimated prevalence of symptoms potentially associated with ovarian cancer was high, even when limiting duration to the window defined for the ongoing DOVE Study (14). Yet the prevalence of ovarian cancer in DOVE was 0.76% in the pilot phase (14), about 10 times that found at the entry examination in large screening
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Table 4. Distributions of Sociodemographic Characteristics and Health-Care Utilization in Mail-Survey Responders and the Target Population, Montreal, Quebec, Canada, 2014–2015 Characteristic
Responders (n = 771) b
Target Populationa No.
%b
40.8
1145
39.5
30.9
867
29.9
14.9
18.5
538
18.5
41
5.3
9.8
352
12.1
French
639
82.9
81.0
2352
81.1
English
132
17.1
19.0
550
19.0
Montreal Island
308
40.0
42.0
1251
43.2
Montreal suburbs
315
40.9
37.9
1057
36.5
Small towns and rural areas
147
19.1
20.2
591
20.4
1 (least deprived)
207
26.9
21.9
628
21.7
2
171
22.2
19.0
565
19.5
3
131
17.0
18.3
538
18.6
4
127
16.5
17.4
507
17.5
97
12.6
17.1
467
16.1
1 (least deprived)
149
19.4
16.4
473
16.3
2
131
17.0
16.0
473
16.3
3
135
17.5
16.9
498
17.2
4
171
22.2
21.6
627
21.6
5 (most deprived)
147
19.1
22.9
634
21.9
37
4.8
6.3
194
6.7
No.
Crude %
Weighted %
50–59
345
44.8
60–69
270
35.0
70–79
115
b
Age, yearsc
≥80 Language
c
Place of residence
c
Material deprivation index
5 (most deprived) Social deprivation indexc
d
Indices not assigned
Health-care utilization in the past 5 yearse >30 general practitioner contactsc
208
27.0
32.2
1033
34.4
>35 specialist contacts
240
31.1
31.4
971
32.4
>1 hospitalization
204
26.5
27.6
895
29.8
75
36.8
43.8
413
46.2
>3 total hospital daysc,f
For comparison of sociodemographic characteristics, the target population was the total eligible population (n = 2,902), which excludes those who reported a bilateral oophorectomy (n = 61), a total hysterectomy (n = 36), or a diagnosis of ovarian cancer (n = 3, of whom 2 reported a bilateral oophorectomy). For comparison of health-care utilization, a second random sample of the 3,000 women was used as the target population. b Values for some categories do not sum to 100% due to rounding. c P < 0.05 for difference between responders and the target population before weighting (χ2 test). d This category includes, for the most part, geographic statistical areas with a high proportion of collective households or institutionalized persons. e Cutoffs represent the averages of the use of health services in the Montreal population of women aged 50 years or older, calculated from the second random sample of 3,000. f Total number of hospital days is reported only among those with at least 1 hospitalization during the previous 5 years. a
trials, and has remained the same with more than 3 times the study population (unpublished data). We found very little evidence that the high prevalence in our survey was caused by low survey response. Prevalence by wave did not suggest meaningful differences in terms of prevalence between early and late responders, contrary to our expectation that having
symptoms would have resulted in early response (29). Furthermore, weighted and unweighted prevalence estimates were very similar for all of the examined combinations of symptoms. Additionally, among the factors that we could examine, only older age was associated with both nonparticipation and symptom reporting. Am J Epidemiol. 2016;184(9):670–680
Estimating Prevalence of Ovarian Cancer Symptoms 677
Table 5. Comparisons of Crude and Weighted Prevalence of Symptoms in a Mail Survey on Ovarian Cancer Symptoms Among Women Aged 50 Years or Older, Montreal, Quebec, Canada, 2014–2015 Crude %
Crude 95% CI
Weighted %a
Weighted 95% CIa
Weighted %b
Weighted 95% CIb
Relative Difference (crude %/weighted %b)
≥1 symptom
81.5
78.5, 84.1
79.7
76.5, 83.1
79.7
76.3, 82.7
1.02
≥3 symptoms
65.4
61.9, 68.7
62.6
58.8, 66.6
63.1
59.2, 66.7
1.04
≥1 symptom within defined duration windowc
59.7
56.1, 63.2
59.0
55.2, 63.0
59.1
55.2, 62.8
1.01
≥1 frequent or severe symptom within defined duration windowd
41.6
38.1, 45.2
41.5
37.8, 45.5
41.9
38.2, 45.7
0.99
Prevalence
Abbreviation: CI, confidence interval. Weighted with sociodemographic characteristics only. b Weighted with sociodemographic characteristics and health-care utilization. c The duration window was defined as at least 2 weeks and less than 1 year, as specified in the Diagnosing Ovarian Cancer Early Study. d This category refers to symptoms that are frequent or severe and that lasted for more than 2 weeks and less than 1 year. a
The most common reason given by women who contacted us to decline participation was having had a total hysterectomy (25%). Technically, a total hysterectomy does not include a bilateral oophorectomy, but this is how it is generally interpreted by women. Given that having at least 1 ovary was an inclusion criterion, it is not surprising that, among eligible responders, a smaller proportion reported having had a hysterectomy than that estimated for Quebec (11% in our study vs. 20% in Quebec among 50to 59-year-olds; and 25% vs. 36.5%, respectively, among
Prevalence, %
A)
60- to 69-year-olds) (37). Based on US estimates, about two-thirds of women undergoing a hysterectomy after age 50 have a concomitant bilateral oophorectomy (38). Therefore, assuming that at least 21% of the 3,000 women would not have had ovaries (37, 38) and about 3% would not have received the survey due to death or having moved (39, 40), the conservatively adjusted response rate would be closer to 34%. The predictors of nonresponse observed in this study— older age and higher deprivation indices—are similar to
60 50 40 30 20 10 0 Lower Back Pain
Gas
Abdominal Bloating
Abdomina Distensionl
Frequent Urination
Leaking Urine
Frequent Urination
Leaking Urine
Symptom
Prevalence, %
B)
60 50 40 30 20 10 0 Lower Back Pain
Gas
Abdominal Bloating
Abdominal Distension
Symptom Figure 1. Comparisons of crude and weighted prevalence for the 6 most common symptoms of ovarian cancer in a mail survey of women aged 50 years or older, Montreal, Quebec, Canada, 2014–2015. A) Prevalence of symptoms of any duration; B) prevalence of symptoms reported as lasting more than 2 weeks and less than 1 year. Black bars: crude prevalence. Gray bars: prevalence weighted with sociodemographic characteristics only. White bars: prevalence weighted with sociodemographic characteristics and health-care utilization. Lower back pain includes pressure in the lower back. Gas includes burping and belching.
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those identified in 2 other studies of cancer symptoms (13, 15). Our findings additionally suggest that responders were somewhat healthier than members of the general population, based on their use of health-care services in the past 5 years. A higher proportion of women in the survey reported their health as excellent or very good compared with women of similar age in Quebec in 2014 (aged 50–64 years: 65.1% vs. 58.2%; aged ≥65 years: 56.8% vs. 43.2%). (41). Not unexpectedly, late responders were more likely to be nonwhite, have a lower to middle household income, and report poorer health. While sending 2 reminders resulted in a slightly higher response among women from more disadvantaged groups, it had little impact on the estimated prevalence. Similar to our findings, sending multiple mailings or conducting a telephone follow-up had little effect on prevalence estimates and on exposuredisease associations (20, 21); however, in one study, the multiple waves increased bias due to reporting errors (22). Three studies have investigated the prevalence of gynecological symptoms in population-based settings (9, 11, 13), with a higher response rate than ours (approximately 50%). Each study inquired about a somewhat different set of symptoms, with different recall intervals (4 weeks, 3 months, or 1 year) and among different age ranges, which makes direct comparisons difficult. All of those studies, and 2 in particular (9, 11), reported a high prevalence. For example, bloating was reported by 40% of Australian women aged 50–70 years when asked about symptoms in the prior year (11) and by 32% of Danish women aged 40 years or older when asked about symptoms in the preceding 4 weeks (9). In the present study, 40% of women 50 years of age or older reported bloating regardless of duration, but only 17% reported that symptom within the DOVE duration window. Abdominal distension was reported by 15% of the Danish women (9) and by 15% of British women aged 45 years or older when asked about symptoms in the prior 3 months (13), compared with 37% in the present study overall (and 18% in the DOVE duration window). Older women reported fewer symptoms in all 3 studies (9, 11, 13). We presented results on symptoms regardless of duration because we expected these estimates to be affected by nonresponse more often than eligible symptoms would be. However, we saw very little evidence of bias due to nonresponse in either category. We cannot rule out the possibility that IPW, based on the limited number of variables available for the entire sample, failed to correct for nonresponse. For example, we did not have individual socioeconomic variables or lifestyle factors for nonresponders, and these factors are generally associated with both nonresponse and health problems (23). However, we obtained deprivation indices, which reflect area-based socioeconomic status and have been found to be strongly associated with indicators of population health, such as age-specific mortality, disability, and the prevalence of several diseases (42). We did not have direct information on health-care utilization in nonresponders, but we had data for responders and for a second random sample of the general population, which we used to apply IPW to reweight responders. Because many studies would not have access to health-care utilization data, we examined whether weighting with only sociodemographic
factors yielded different results than when also accounting for health-care utilization, but we saw no difference. Low response is a common problem in health studies, particularly challenging in surveys aimed at estimating prevalence of conditions not recorded in administrative registries. Estimates from such surveys are often the only information available, and researchers must try to assess the extent of bias. In this survey, as in others, nonresponders were more likely to be older and to live in more deprived residential areas. It is worth noting, however, that ovarian cancer is more common among white women and women of high socioeconomic status (43). Although sending multiple mailings yielded a higher proportion of responses from women from less privileged socioeconomic strata, prevalence was not lower among late responders. Adjustment by IPW had a minimal impact on the prevalence estimates. Overall, the effect of low response on the estimated prevalence appeared to be very small. Ours is, to our knowledge, the first study to assess the prevalence of symptoms that, when applied prospectively to the general population, identify a subgroup with a “high” prevalence of ovarian cancer. Nevertheless, these symptoms, even when constrained to a specific duration window, are still too common to be used outside the context of a research study. Only when DOVE is concluded will we be able to refine the symptom criteria that may be implemented in clinical practice to trigger diagnostic testing.
ACKNOWLEDGMENTS
Author affiliations: Department of Epidemiology, Biostatistics and Occupational Health, Faculty of Medicine, McGill University, Montreal, Quebec, Canada (Zhuoyu Sun, Antonio Ciampi, Jay S. Kaufman, Olga Basso); Department of Obstetrics and Gynecology, Faculty of Medicine, Research Institute of the McGill University Health Center, Montreal, Quebec, Canada (Lucy Gilbert, Olga Basso); and Department of Oncology, Faculty of Medicine, McGill University, Montreal, Quebec, Canada (Lucy Gilbert). This study was supported by the Diagnosing Ovarian Cancer Early Fund, which includes funding from the Canadian Institutes of Health Research (grant 123529), the Royal Victoria Hospital Foundation, the Carole Epstein Foundation, the Montreal General Hospital Foundation, and private donors. Z.S. has received a doctoral training award from the Fonds de Recherche du Québec—Santé. We thank Philippe Gamache from the Institut National de Santé Publique du Québec for generating deprivation indices and Debbie Manessis and the Diagnosing Ovarian Cancer Early team for invaluable assistance with the survey. Conflict of interest: none declared.
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Vol. 184, No. 9 DOI: 10.1093/aje/kww086 Advance Access publication: October 13, 2016
Practice of Epidemiology Estimating the Prevalence of Ovarian Cancer Symptoms in Women Aged 50 Years or Older: Problems and Possibilities
Zhuoyu Sun*, Lucy Gilbert, Antonio Ciampi, Jay S. Kaufman, and Olga Basso * Correspondence to Zhuoyu Sun, Department of Epidemiology, Biostatistics and Occupational Health, Faculty of Medicine, McGill University, 1020 Pine Avenue West, Montreal, Quebec H3A 1A2, Canada (e-mail: [email protected]).
Initially submitted December 3, 2015; accepted for publication February 2, 2016.
Diagnostic testing is recommended in women with “ovarian cancer symptoms.” However, these symptoms are nonspecific. The ongoing Diagnosing Ovarian Cancer Early (DOVE) Study in Montreal, Quebec, Canada, provides diagnostic testing to women aged 50 years or older with symptoms lasting for more than 2 weeks and less than 1 year. The prevalence of ovarian cancer in DOVE is 10 times that of large screening trials, prompting us to estimate the prevalence of these symptoms in this population. We sent a questionnaire to 3,000 randomly sampled women in 2014–2015. Overall, 833 women responded; 81.5% reported at least 1 symptom, and 59.7% reported at least 1 symptom within the duration window specified in DOVE. We explored whether such high prevalence resulted from low survey response by applying inverse probability weighting to correct the estimates. Older women and those from deprived areas were less likely to respond, but only age was associated with symptom reporting. Prevalence was similar in early and late responders. Inverse probability weighting had a minimal impact on estimates, suggesting little evidence of nonresponse bias. This is the first study investigating symptoms that have proven to identify a subset of women with a high prevalence of ovarian cancer. However, the high frequency of symptoms warrants further refinements before symptom-triggered diagnostic testing can be implemented. mail survey; nonresponse; nonresponse bias; ovarian cancer symptoms; prevalence
Abbreviations: DOVE, Diagnosing Ovarian Cancer Early; IPW, inverse probability weighting.
Although long considered a “silent killer,” ovarian cancer is often preceded by symptoms (1–7); this realization has led to the recommendation that women experiencing certain symptoms be tested to rule out ovarian cancer (8). However, the symptoms associated with ovarian cancer are common and nonspecific (3, 7, 9–11), and diagnostic tests for ovarian cancer have low sensitivity and specificity (12), which makes it unfeasible to investigate all symptomatic women (13). The ongoing Diagnosing Ovarian Cancer Early (DOVE) Study in Montreal, Quebec, Canada, has the objective of evaluating whether prompt assessment of symptomatic women aged 50 years or older results in earlier diagnosis of ovarian cancer and, ultimately, better prognosis (14). In the absence of rigorous prospective data, admission to DOVE was not determined by type, frequency, or
severity of symptoms. The only criterion imposed was that of duration, to avoid inclusion of transitory conditions on the one end and chronic conditions on the other. Thus, women were eligible for admission to DOVE if their symptoms had lasted more than 2 weeks and less than 1 year. The prevalence of invasive ovarian cancer in DOVE is about 10 times that observed at the first visit of large ovarian cancer screening trials (14). This finding prompted us to assess the prevalence of “ovarian cancer symptoms” in this population. We sent a questionnaire to a random sample of 3,000 women aged 50 years or older living in Montreal and up to 2 reminders to nonresponders. The crude response rate was 28%. Among eligible responders, 81.5% reported at least 1 symptom. The prevalence was reduced to 59.7% when restricted to the duration window specified in the
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DOVE Study—still too high to trigger widespread diagnostic testing. On the other hand, this high prevalence may be due to the low response rate. Low response is a frequent problem in health surveys. Certain segments of the population, such as older individuals and those with lower socioeconomic status (13, 15), are particularly less likely to respond. If response is associated with having the condition(s) of interest, prevalence estimates can be severely affected by low response (16, 17). However, the response rate per se is a poor predictor of the magnitude of bias (18); more important is the extent to which nonresponse is associated with determinants of the outcome under study. For instance, in a survey with a response rate of 26%, Grievink et al. (19) did not find nonresponse to bias the estimated prevalence of the examined health conditions. In other studies, it was shown that increasing response rates by sending multiple mailings had little effect on prevalence (20, 21), but it increased bias due to reporting errors (22). However, the implications of low response have to be assessed on a case-by-case basis. Postsurvey adjustments (e.g., inverse probability weighting) are often applied to correct for nonresponse (23–26). In this study, we investigated the impact of nonresponse on the prevalence of “ovarian cancer symptoms” estimated from our survey and discuss the implications of diagnostic testing for ovarian cancer in symptomatic women. METHODS Questionnaire and study population
The questionnaire used in this survey was developed and pretested in an academic setting and included the symptoms determining eligibility for the DOVE Study (14). We pilot tested the questionnaire among 30 women aged 50 years or older who attended public presentations about DOVE, and we revised it based on poor completion and response time. The study population consisted of 3,000 women aged 50 years or older, living in the Greater Montreal area, randomly sampled among those covered by the Régie de l’Assurance Maladie du Québec (Quebec Health Insurance Plan), which covers virtually all Quebec residents. We obtained the names, preferred language, and addresses of the women and, in July 2014, we sent a mail package in French or English, containing a cover letter, the informed consent form, login details (for responders to reply online if they preferred), the questionnaire, and a prepaid return envelope. All responders were entered into a drawing to win a $100 gift card (one for every 200 participants who returned the questionnaire). Nonresponders were sent a reminder letter 7 weeks after the initial mailing and a second letter after a further 9 weeks. Women responding to the first, second, and third mailings were considered early, intermediate, and late responders, respectively. The study was approved by the institutional ethics review board of McGill University and the Commission d’Accès à l’Information du Québec. The questionnaire included questions about symptoms, sociodemographic characteristics (age, race/ethnicity, education, income, and marital and employment status), smoking status, and medical history (family history of cancer and Am J Epidemiol. 2016;184(9):670–680
cancer diagnosis), and responders were asked to rate their health status. The 31 symptoms were divided into 7 groups (see Web Appendix 1, available at http://aje.oxfordjournals. org/). Responders were asked to report the severity (from low to high on a scale of 1 to 5) and frequency of the symptom (all the time, daily, weekly, or monthly), as well as duration ( 0.2) (32). In the second step, using the IPW method, we reweighted survey responders up to the second sample of 3,000 to achieve representativeness with respect to health-care use (33). To avoid extreme weights, which can result in unstable estimates, we truncated weights below the first percentile and above the 99th percentile by setting them at the values of the first and 99th percentiles, respectively (34, 35). We then compared the preand postweighted data with the 2 random samples, with respect to sociodemographic factors (the entire eligible sample) and use of health-care services (the second sample, provided for this purpose). We used a robust, sandwich-type variance estimator to account for the fact that the weights were estimated (36). All analyses were carried out using SAS, version 9.3 (SAS Institute, Inc., Cary, North Carolina).
Table 1. Sociodemographic Characteristics of Responders and Nonresponders and Predictors of Nonresponse in a Mail Survey on Ovarian Cancer Symptoms Among Women Aged 50 Years or Older, Montreal, Quebec, Canada, 2014–2015 Characteristic
Responders (n = 771)
Nonresponders (n = 2,131)
No.
%a
%a
RRb
50–59
345
44.8
60–69
270
35.0
800
37.5
1.00
597
28.0
0.97
70–79
115
14.9
423
19.9
1.10
1.04, 1.17
41
5.3
311
14.6
1.22
1.16, 1.30
French
639
82.9
1713
80.4
1.00
0.74, 1.03
English
132
17.1
418
19.6
1.04
0.99, 1.10
Montreal Island
308
40.0
943
44.3
1.00
Suburbs
315
40.9
742
34.9
0.98
0.93, 1.03
Small towns and rural areas
147
19.1
444
20.9
1.01
0.95, 1.07
1 (least deprived)
207
26.9
421
19.8
1.00
2
171
22.2
394
18.5
1.06
1.00, 1.14
3
131
17.0
407
19.1
1.13
1.05, 1.21
4
127
16.5
380
17.9
1.13
1.05, 1.22
97
12.6
370
17.4
1.17
1.09, 1.25
1 (least deprived)
149
19.4
324
15.2
1.00
2
131
17.0
342
16.1
1.05
0.97, 1.14
3
135
17.5
363
17.1
1.04
0.96, 1.13
4
171
22.2
456
21.4
1.02
0.95, 1.10
5 (most deprived)
147
19.1
487
22.9
1.07
1.00, 1.16
Indices not assignedc
37
4.8
157
7.4
1.17
1.06, 1.30
No.
95% CI
Age, years
≥80
0.92, 1.03
Language
Place of residence
Material deprivation index
5 (most deprived) Social deprivation index
Abbreviations: CI, confidence interval; RR, relative risk. Values for some categories do not sum to 100% due to rounding. b RRs were adjusted for all other variables in the table. c This category includes, for the most part, geographic statistical areas with a high proportion of collective households or institutionalized persons. a
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RESULTS
We received 389 responses to the first wave of the survey, 303 to the second, and 141 to the third (with 25, 60, and 61 women, respectively, calling to decline participation at each wave). In total, 833 out of 3,000 women returned a
completed questionnaire (response rate = 28%). Only 7% answered online. Among responders, 62 (7.4%) reported a bilateral oophorectomy or a previous diagnosis of ovarian cancer, which made them ineligible for the study. There were 771 eligible responders. We also excluded from the total sample 36 of the 146 women who contacted us,
Table 2. Associations Between Sociodemographic Characteristics, Health-Care Use, and Reporting of at Least 1 Symptom (in the Defined Duration Windowa) Among Responders in a Mail Survey on Ovarian Cancer Symptoms Among Women Aged 50 Years or Older, Montreal, Quebec, Canada, 2014–2015
Characteristic
Responders With ≥1 Symptom (n = 628) No.
%b
RRc
50–59
288
83.5
1.00
60–69
222
82.2
70–79
89
≥80
Responders With ≥1 Symptom in Defined Duration Window (n = 460) %b
RRc
95% CI
No.
95% CI
209
60.6
1.00
1.00
0.93, 1.06
164
60.7
0.97
0.85, 1.10
77.4
0.92
0.83, 1.03
64
55.7
0.84
0.70, 1.00
29
70.7
0.82
0.68, 1.00
23
56.1
0.95
0.72, 1.25
French
523
81.9
1.00
English
105
79.6
0.99
Montreal Island
250
81.2
1.00
Suburbs
262
83.2
Small towns and rural areas
116
1 (least deprived) 2 3 4
Age, years
Language 381
59.6
1.00
0.90, 1.09
79
59.9
0.99
179
58.1
1.00
1.03
0.96, 1.10
196
62.2
1.08
0.95, 1.22
78.9
0.97
0.89, 1.05
85
57.8
1.03
0.87, 1.21
173
83.6
1.00
124
59.9
1.00
140
81.9
0.98
0.91, 1.06
104
60.8
1.02
0.87, 1.20
111
84.7
0.98
0.90, 1.08
82
62.6
1.06
0.90, 1.25
100
78.7
0.96
0.86, 1.06
78
61.4
1.05
0.89, 1.25
75
77.3
0.94
0.85, 1.04
52
53.6
0.91
0.74, 1.13
1 (least deprived)
126
84.6
1.00
90
60.4
1.00
2
108
82.4
0.97
0.88, 1.06
79
60.3
1.02
0.85, 1.23
3
113
83.7
0.99
0.90, 1.09
83
61.5
1.06
0.88, 1.27
4
140
81.9
0.97
0.88, 1.06
98
57.3
0.94
0.79, 1.13
5 (most deprived)
112
76.2
0.93
0.84, 1.03
90
61.2
1.05
0.88, 1.26
29
78.4
0.98
0.82, 1.17
20
54.1
0.94
0.68, 1.30
0.85, 1.15
Place of residence
Material deprivation index
5 (most deprived) Social deprivation index
d
Indices not assigned
Health-care utilization in the previous 5 yearse >30 general practitioner contacts
176
84.6
1.05
0.98, 1.13
135
64.9
1.12
1.00, 1.27
>35 specialist contacts
207
86.3
1.09
1.02, 1.16
162
67.5
1.20
1.07, 1.35
>1 hospitalization
170
83.3
1.01
0.94, 1.08
129
63.2
1.08
0.96, 1.23
59
78.7
0.91
0.80, 1.05
45
60.0
0.92
0.74, 1.15
>3 total hospital daysf
Abbreviations: CI, confidence interval; RR, relative risk. The duration window was defined as at least 2 weeks and less than 1 year, as specified in the Diagnosing Ovarian Cancer Early Study. b Percentage of women reporting symptoms in each row. c RRs were adjusted for all other variables in the table. d This category includes, for the most part, geographic statistical areas with a high proportion of collective households or institutionalized persons. e Cutoffs represent the averages of the use of health services in the Montreal population of women aged 50 years or older, calculated from the second random sample of 3,000. f Total number of hospital days is reported only among those with at least 1 hospitalization during the previous 5 years. a
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Table 3. Characteristics Among Subgroups of Responders in a Mail Survey on Ovarian Cancer Symptoms Among Women Aged 50 Years or Older, Montreal, Quebec, Canada, 2014–2015
Characteristic
Early Responders (n = 368)
Intermediate Responders (n = 274) %a
Late Responders (n = 129)
No.
%a
No.
50–59
164
44.6
126
46.0
55
42.6
60–69
134
36.4
86
31.4
50
38.8
70–79
57
15.5
41
15.0
17
13.2
≥80
13
3.5
21
7.7
7
5.4
355
96.7
248
90.8
114
88.4
12
3.3
25
9.2
15
11.6
French
306
83.2
225
82.1
108
83.7
English
62
16.9
49
17.9
21
16.3
Montreal Island
143
39.0
114
41.6
51
39.5
Suburbs
161
43.9
106
38.7
48
37.2
63
17.2
54
19.7
30
23.3
High school or less
128
34.9
115
42.0
55
42.6
College or technical school
102
27.8
68
24.8
32
24.8
University
137
37.3
91
33.2
42
32.6
No.
%a
Age, years
Race/ethnicityb White Nonwhite Language
Place of residence
Small towns and rural areas Educational level
Marital status Single
42
11.4
29
10.6
13
10.2
235
63.9
173
63.4
73
57.0
91
24.7
71
26.0
42
32.8
Employed
161
43.8
101
36.9
47
36.4
Retired
160
43.5
119
43.4
59
45.7
47
12.8
54
19.7
23
17.8 17.1
Married or common-law partner Separated, divorced, or widowed Employment status
Other Annual household income, Canadian dollarsb 30 general practitioner contacts
100
27.2
>35 specialist contacts
Intermediate Responders (n = 274) No.
%a
Late Responders (n = 129) No.
%a
d
Health-care utilization in the past 5 years
78
28.5
30
23.3
107
29.1
89
32.5
44
34.1
>1 hospitalization
93
25.3
76
27.7
35
27.1
>3 total hospital dayse
32
34.4
30
39.5
13
37.1
≥1 symptom
301
81.8
221
80.7
106
82.2
≥1 symptom within defined durationf
219
59.5
159
58.0
82
63.6
≥3 symptoms
242
65.8
173
63.1
89
69.0
≥1 frequent or severe symptom within defined durationg
146
39.7
112
40.9
63
48.8
Presence of symptoms
a
Values for some categories do not sum to 100% due to rounding. P < 0.05 for difference between early, intermediate, and late responders (χ2 tests). c This category refers to family history of ovarian, breast, and colon cancer. d Cutoffs represent the averages of the use of health services in the Montreal population of women aged 50 years or older, calculated from the second random sample of 3,000. e Total number of hospital days is reported only among those with at least 1 hospitalization during the previous 5 years. f The duration window was defined as at least 2 weeks and less than 1 year, as specified in the Diagnosing Ovarian Cancer Early Study. g This category refers to symptoms that are frequent or severe and that lasted for more than 2 weeks and less than 1 year. b
because they reported having had a “total” hysterectomy. After these exclusions, we had 2,902 eligible responders for analysis, although the true number of eligible responders (with at least 1 ovary and no prior diagnosis of ovarian cancer) would be lower. The average age of responders was 62 years (range, 50– 98 years). Response rates were significantly lower among women aged 70 years or older, women living in Montreal Island or rural areas, and women with higher material or social deprivation indices (Table 1). In multivariate analyses, only older age and living in more materially or socially deprived areas were significantly associated with nonresponse. In total, 81.5% of women reported at least 1 symptom, regardless of duration, and 59.7% reported 1 or more symptoms within the DOVE duration window. Younger age, but not deprivation index, was independently associated with reporting at least 1 symptom. Additionally, symptomatic women reported a higher use of health-care services in the previous 5 years (Table 2). Patterns were similar for reporting at least 1 symptom in the DOVE duration window (as well as for reporting ≥3 symptoms or ≥1 frequent or severe symptom in the DOVE duration window; see Web Table 1). When we tested the model without health-care use, results were unchanged. Compared with early responders, a higher proportion of intermediate and late responders were nonwhite, had an annual household income less than $50,000 (in Canadian dollars), and reported fair or poor health (as opposed to excellent or good health) (Table 3). There were no significant differences in health-care utilization between early and late responders. Prevalence of symptoms did not decline by wave of response. On the contrary, late responders more Am J Epidemiol. 2016;184(9):670–680
often reported having a frequent or severe symptom in the DOVE duration window. As shown in Table 4, before weighting, responders were more likely to be younger, living in the suburbs, and from more materially or socially privileged areas than the target population. In addition, responders had fewer than average contacts with their general practitioners and, if hospitalized in the past 5 years, spent fewer days in the hospital. After IPW adjustment, responders were more comparable to the target population with respect to sociodemographic factors and health-care use. The covariates retained in the final models are listed in Web Table 2. The overall prevalence of symptoms changed very little after weighting, either by sociodemographic factors or by sociodemographic factors and health-care utilization (Table 5; distribution of weights is shown in Web Figure 1). To check whether model selection affected the estimates, we repeated the analyses including all covariates and found no material difference (data not shown). The crude and weighted prevalence of the 6 most frequent symptoms differed considerably depending on whether or not they fell into the DOVE duration window (Figure 1).
DISCUSSION
In this study, the estimated prevalence of symptoms potentially associated with ovarian cancer was high, even when limiting duration to the window defined for the ongoing DOVE Study (14). Yet the prevalence of ovarian cancer in DOVE was 0.76% in the pilot phase (14), about 10 times that found at the entry examination in large screening
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Table 4. Distributions of Sociodemographic Characteristics and Health-Care Utilization in Mail-Survey Responders and the Target Population, Montreal, Quebec, Canada, 2014–2015 Characteristic
Responders (n = 771) b
Target Populationa No.
%b
40.8
1145
39.5
30.9
867
29.9
14.9
18.5
538
18.5
41
5.3
9.8
352
12.1
French
639
82.9
81.0
2352
81.1
English
132
17.1
19.0
550
19.0
Montreal Island
308
40.0
42.0
1251
43.2
Montreal suburbs
315
40.9
37.9
1057
36.5
Small towns and rural areas
147
19.1
20.2
591
20.4
1 (least deprived)
207
26.9
21.9
628
21.7
2
171
22.2
19.0
565
19.5
3
131
17.0
18.3
538
18.6
4
127
16.5
17.4
507
17.5
97
12.6
17.1
467
16.1
1 (least deprived)
149
19.4
16.4
473
16.3
2
131
17.0
16.0
473
16.3
3
135
17.5
16.9
498
17.2
4
171
22.2
21.6
627
21.6
5 (most deprived)
147
19.1
22.9
634
21.9
37
4.8
6.3
194
6.7
No.
Crude %
Weighted %
50–59
345
44.8
60–69
270
35.0
70–79
115
b
Age, yearsc
≥80 Language
c
Place of residence
c
Material deprivation index
5 (most deprived) Social deprivation indexc
d
Indices not assigned
Health-care utilization in the past 5 yearse >30 general practitioner contactsc
208
27.0
32.2
1033
34.4
>35 specialist contacts
240
31.1
31.4
971
32.4
>1 hospitalization
204
26.5
27.6
895
29.8
75
36.8
43.8
413
46.2
>3 total hospital daysc,f
For comparison of sociodemographic characteristics, the target population was the total eligible population (n = 2,902), which excludes those who reported a bilateral oophorectomy (n = 61), a total hysterectomy (n = 36), or a diagnosis of ovarian cancer (n = 3, of whom 2 reported a bilateral oophorectomy). For comparison of health-care utilization, a second random sample of the 3,000 women was used as the target population. b Values for some categories do not sum to 100% due to rounding. c P < 0.05 for difference between responders and the target population before weighting (χ2 test). d This category includes, for the most part, geographic statistical areas with a high proportion of collective households or institutionalized persons. e Cutoffs represent the averages of the use of health services in the Montreal population of women aged 50 years or older, calculated from the second random sample of 3,000. f Total number of hospital days is reported only among those with at least 1 hospitalization during the previous 5 years. a
trials, and has remained the same with more than 3 times the study population (unpublished data). We found very little evidence that the high prevalence in our survey was caused by low survey response. Prevalence by wave did not suggest meaningful differences in terms of prevalence between early and late responders, contrary to our expectation that having
symptoms would have resulted in early response (29). Furthermore, weighted and unweighted prevalence estimates were very similar for all of the examined combinations of symptoms. Additionally, among the factors that we could examine, only older age was associated with both nonparticipation and symptom reporting. Am J Epidemiol. 2016;184(9):670–680
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Table 5. Comparisons of Crude and Weighted Prevalence of Symptoms in a Mail Survey on Ovarian Cancer Symptoms Among Women Aged 50 Years or Older, Montreal, Quebec, Canada, 2014–2015 Crude %
Crude 95% CI
Weighted %a
Weighted 95% CIa
Weighted %b
Weighted 95% CIb
Relative Difference (crude %/weighted %b)
≥1 symptom
81.5
78.5, 84.1
79.7
76.5, 83.1
79.7
76.3, 82.7
1.02
≥3 symptoms
65.4
61.9, 68.7
62.6
58.8, 66.6
63.1
59.2, 66.7
1.04
≥1 symptom within defined duration windowc
59.7
56.1, 63.2
59.0
55.2, 63.0
59.1
55.2, 62.8
1.01
≥1 frequent or severe symptom within defined duration windowd
41.6
38.1, 45.2
41.5
37.8, 45.5
41.9
38.2, 45.7
0.99
Prevalence
Abbreviation: CI, confidence interval. Weighted with sociodemographic characteristics only. b Weighted with sociodemographic characteristics and health-care utilization. c The duration window was defined as at least 2 weeks and less than 1 year, as specified in the Diagnosing Ovarian Cancer Early Study. d This category refers to symptoms that are frequent or severe and that lasted for more than 2 weeks and less than 1 year. a
The most common reason given by women who contacted us to decline participation was having had a total hysterectomy (25%). Technically, a total hysterectomy does not include a bilateral oophorectomy, but this is how it is generally interpreted by women. Given that having at least 1 ovary was an inclusion criterion, it is not surprising that, among eligible responders, a smaller proportion reported having had a hysterectomy than that estimated for Quebec (11% in our study vs. 20% in Quebec among 50to 59-year-olds; and 25% vs. 36.5%, respectively, among
Prevalence, %
A)
60- to 69-year-olds) (37). Based on US estimates, about two-thirds of women undergoing a hysterectomy after age 50 have a concomitant bilateral oophorectomy (38). Therefore, assuming that at least 21% of the 3,000 women would not have had ovaries (37, 38) and about 3% would not have received the survey due to death or having moved (39, 40), the conservatively adjusted response rate would be closer to 34%. The predictors of nonresponse observed in this study— older age and higher deprivation indices—are similar to
60 50 40 30 20 10 0 Lower Back Pain
Gas
Abdominal Bloating
Abdomina Distensionl
Frequent Urination
Leaking Urine
Frequent Urination
Leaking Urine
Symptom
Prevalence, %
B)
60 50 40 30 20 10 0 Lower Back Pain
Gas
Abdominal Bloating
Abdominal Distension
Symptom Figure 1. Comparisons of crude and weighted prevalence for the 6 most common symptoms of ovarian cancer in a mail survey of women aged 50 years or older, Montreal, Quebec, Canada, 2014–2015. A) Prevalence of symptoms of any duration; B) prevalence of symptoms reported as lasting more than 2 weeks and less than 1 year. Black bars: crude prevalence. Gray bars: prevalence weighted with sociodemographic characteristics only. White bars: prevalence weighted with sociodemographic characteristics and health-care utilization. Lower back pain includes pressure in the lower back. Gas includes burping and belching.
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those identified in 2 other studies of cancer symptoms (13, 15). Our findings additionally suggest that responders were somewhat healthier than members of the general population, based on their use of health-care services in the past 5 years. A higher proportion of women in the survey reported their health as excellent or very good compared with women of similar age in Quebec in 2014 (aged 50–64 years: 65.1% vs. 58.2%; aged ≥65 years: 56.8% vs. 43.2%). (41). Not unexpectedly, late responders were more likely to be nonwhite, have a lower to middle household income, and report poorer health. While sending 2 reminders resulted in a slightly higher response among women from more disadvantaged groups, it had little impact on the estimated prevalence. Similar to our findings, sending multiple mailings or conducting a telephone follow-up had little effect on prevalence estimates and on exposuredisease associations (20, 21); however, in one study, the multiple waves increased bias due to reporting errors (22). Three studies have investigated the prevalence of gynecological symptoms in population-based settings (9, 11, 13), with a higher response rate than ours (approximately 50%). Each study inquired about a somewhat different set of symptoms, with different recall intervals (4 weeks, 3 months, or 1 year) and among different age ranges, which makes direct comparisons difficult. All of those studies, and 2 in particular (9, 11), reported a high prevalence. For example, bloating was reported by 40% of Australian women aged 50–70 years when asked about symptoms in the prior year (11) and by 32% of Danish women aged 40 years or older when asked about symptoms in the preceding 4 weeks (9). In the present study, 40% of women 50 years of age or older reported bloating regardless of duration, but only 17% reported that symptom within the DOVE duration window. Abdominal distension was reported by 15% of the Danish women (9) and by 15% of British women aged 45 years or older when asked about symptoms in the prior 3 months (13), compared with 37% in the present study overall (and 18% in the DOVE duration window). Older women reported fewer symptoms in all 3 studies (9, 11, 13). We presented results on symptoms regardless of duration because we expected these estimates to be affected by nonresponse more often than eligible symptoms would be. However, we saw very little evidence of bias due to nonresponse in either category. We cannot rule out the possibility that IPW, based on the limited number of variables available for the entire sample, failed to correct for nonresponse. For example, we did not have individual socioeconomic variables or lifestyle factors for nonresponders, and these factors are generally associated with both nonresponse and health problems (23). However, we obtained deprivation indices, which reflect area-based socioeconomic status and have been found to be strongly associated with indicators of population health, such as age-specific mortality, disability, and the prevalence of several diseases (42). We did not have direct information on health-care utilization in nonresponders, but we had data for responders and for a second random sample of the general population, which we used to apply IPW to reweight responders. Because many studies would not have access to health-care utilization data, we examined whether weighting with only sociodemographic
factors yielded different results than when also accounting for health-care utilization, but we saw no difference. Low response is a common problem in health studies, particularly challenging in surveys aimed at estimating prevalence of conditions not recorded in administrative registries. Estimates from such surveys are often the only information available, and researchers must try to assess the extent of bias. In this survey, as in others, nonresponders were more likely to be older and to live in more deprived residential areas. It is worth noting, however, that ovarian cancer is more common among white women and women of high socioeconomic status (43). Although sending multiple mailings yielded a higher proportion of responses from women from less privileged socioeconomic strata, prevalence was not lower among late responders. Adjustment by IPW had a minimal impact on the prevalence estimates. Overall, the effect of low response on the estimated prevalence appeared to be very small. Ours is, to our knowledge, the first study to assess the prevalence of symptoms that, when applied prospectively to the general population, identify a subgroup with a “high” prevalence of ovarian cancer. Nevertheless, these symptoms, even when constrained to a specific duration window, are still too common to be used outside the context of a research study. Only when DOVE is concluded will we be able to refine the symptom criteria that may be implemented in clinical practice to trigger diagnostic testing.
ACKNOWLEDGMENTS
Author affiliations: Department of Epidemiology, Biostatistics and Occupational Health, Faculty of Medicine, McGill University, Montreal, Quebec, Canada (Zhuoyu Sun, Antonio Ciampi, Jay S. Kaufman, Olga Basso); Department of Obstetrics and Gynecology, Faculty of Medicine, Research Institute of the McGill University Health Center, Montreal, Quebec, Canada (Lucy Gilbert, Olga Basso); and Department of Oncology, Faculty of Medicine, McGill University, Montreal, Quebec, Canada (Lucy Gilbert). This study was supported by the Diagnosing Ovarian Cancer Early Fund, which includes funding from the Canadian Institutes of Health Research (grant 123529), the Royal Victoria Hospital Foundation, the Carole Epstein Foundation, the Montreal General Hospital Foundation, and private donors. Z.S. has received a doctoral training award from the Fonds de Recherche du Québec—Santé. We thank Philippe Gamache from the Institut National de Santé Publique du Québec for generating deprivation indices and Debbie Manessis and the Diagnosing Ovarian Cancer Early team for invaluable assistance with the survey. Conflict of interest: none declared.
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