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International Journal of Gynecological Cancer:
Original Article

Comorbidity and ovarian cancer survival in Denmark, 1995–2005: a population‐based cohort study

TETSCHE, M. S.*,†; NØRGAARD, M.*; JACOBSEN, J.*; WOGELIUS, P.*; SØRENSEN, H. T.*

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Author Information

*Department of Clinical Epidemiology, Aarhus University Hospital, Ole Worms Allé, Aarhus, Denmark; and †Department of Gynecology, Aalborg Hospital, Aarhus University Hospital, Reberbansgade, Aalborg, Denmark

Address correspondence and reprint requests to: Mette Skytte Tetsche, MD, Department of Clinical Epidemiology, Aarhus University Hospital, Sdr. Skovvej 15, DK-9000 Aalborg, Denmark. Email: mst@rn.dk

Accepted for publication June 4, 2007

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Abstract

The impact of comorbid diseases on ovarian cancer survival is largely unknown. We therefore examined (i) the prevalence of comorbidity among ovarian cancer patients and (ii) the impact of comorbidity on ovarian cancer survival and mortality. Using hospital discharge data, we identified Danish women diagnosed with ovarian cancer between 1995 and 2005 (n= 1995 within a population of 1.6 million) and then computed Charlson comorbidity index scores (0, 1–2, and 3+). We estimated the prevalence of comorbidity and computed absolute survival and relative mortality rate ratios (MRRs) according to comorbidity level, using patients with Charlson score 0 as the reference group. During the study period, the proportion of patients without comorbidity fell from 81% to 75%, while the proportion of patients with comorbidity score 1–2 and 3+ rose from 16% to 21% and from 4% to 5%, respectively. Overall 1-year survival increased from 68% in 1995–1997 to 70% in 1998–2000 and to 73% in 2001–2004. For patients with Charlson score 1–2, 1-year adjusted MRRs were 1.1 (95% CI, 0.8–1.6) in 1995–1997, 1.3 (95% CI, 1.0–1.8) in 1998–2000, and 1.7 (95% CI, 1.3–2.4) in 2001–2004. For patients with Charlson score 3+, 1-year adjusted MRRs were 2.4 (95% CI, 1.4–4.3) in 1995–1997, 1.6 (95% CI, 1.0–2.7) in 1998–2000, and 2.2 (95% CI, 1.3–3.8) in 2001–2004. The 5-year MRRs were similar to the 1-year MRRs. One quarter of Danish women with ovarian cancer were found to have comorbid conditions, and 5% had severe comorbidity. Severe comorbidity was a predictor of poorer survival.

Ovarian cancer is the leading cause of death among women with gynecological malignancies in the Western world(1). In Europe, 5-year relative survival rates for ovarian cancer range from approximately 26% to 51%(2).

The incidence of ovarian cancer increases sharply with age, as do coexisting diseases(3,4). As our society ages, clinicians will be treating older patients more frequently, with increased likelihood that newly diagnosed ovarian cancer patients will have coexisting diseases. Comorbidity, which refers to one or more coexisting diseases among patients with an index disease, is a well-established prognostic factor for many chronic diseases(5). Whether comorbidity associated with ovarian cancer has a negative impact on prognosis is controversial, since the few existing population-based studies addressing this question are inconclusive(6–9).

The hospital discharge registries (HDRs) in each Danish county provide a unique opportunity to analyze prospectively, in a population-based setting, the impact of comorbidity on survival after cancer. We conducted a population-based study in four Danish counties among women diagnosed with ovarian cancer between 1995 and 2004. Our specific aims were to examine (i) the prevalence of comorbidity from 1995 to 2004 and (ii) the impact of comorbidity on ovarian cancer survival and mortality during the study period.

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Materials and methods

We conducted the study from January 1, 1995, to January 31, 2005, in four counties of Northern Denmark (North Jutland, Aarhus, Viborg, and Ringkjobing), with a total population of approximately 1.6 million inhabitants.

The entire Danish population has free access to tax-supported medical care, including hospitalization. Hospital medical services are primarily population based. In 2004, surgery for ovarian cancer in Denmark took place in 52 hospital departments(10); of these, five were gynecological oncologic centers and two were located in Northern Denmark. Practically, no private inpatient ovarian cancer treatment is available in Denmark.

Denmark's Civil Registration System provided information on vital status, date of death, and place of residence for the women in the study. Since 1968, a unique ten-digit civil registration number has been assigned to each Danish resident by the Central Office of Civil Registration. Use of this number allowed us to link data from several health and demographic registries(11). To be included in our study, patients had to reside in one of the study counties at the time of their ovarian cancer diagnosis. The vital status of all study patients was recorded on February 1, 2005.

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Identification of ovarian cancer patients

We identified ovarian cancer patients through a review of discharge diagnosis codes stored in the Aarhus University Hospital research database. This database contains key information on all patients in the HDRs of the four counties. These registries in turn include information on all patients admitted to nonpsychiatric hospitals in Denmark since 1977. The registries are used routinely to monitor hospital admissions and discharges, waiting lists, operations, and treatment. Registry data include civil registration number (CPR), dates of admission and discharge, surgical procedure(s) performed, and up to 20 discharge diagnoses (provided by physicians), which are classified according to the Danish version of the International Classification of Diseases (ICD) (eighth revision until the end of 1993 and tenth revision thereafter)(12). The ICD-8 codes used to identify incident ovarian cancer cases were 183.00–03 and 183.08–09, and the ICD-10 code used was C56.x. During our study period, the use of stage-specific ICD-10 ovarian cancer codes (C56.0–C56.3) was very limited in the four counties; it was therefore not possible to obtain a valid stage distribution from the HDRs. Our study encompassed all patients registered for the first time with an ovarian cancer discharge diagnosis. To avoid prevalent cases, we excluded patients diagnosed with ovarian cancer between 1977 and 1994.

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Comorbidity

For each ovarian cancer patient, we computed the Charlson comorbidity index score based on discharge diagnoses prior to the ovarian cancer diagnosis using Aarhus University Hospital research database. The Charlson comorbidity index is a weighted index of the number and the seriousness of comorbid diseases(13), widely used in research internationally. The index contains 19 different medical conditions, each weighted according to its potential for influencing mortality. The index score is the sum of these weights. When computing the index score, we only included cancer diagnoses registered more than 60 days before first admittance with ovarian cancer in order to avoid including unspecific cancer diagnoses given in relation to the diagnostic process of ovarian cancer.

We classified the ovarian cancer patients into three groups(13) according to degree of comorbidity: (i) women with a Charlson comorbidity index score of 0, (ii) women with a Charlson comorbidity index score of 1–2, and (iii) women with a Charlson comorbidity index score of 3+.

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Statistical analyses
Prevalence of comorbidity

We computed the occurrence of the 19 discrete medical conditions defined in the Charlson comorbidity index(13) in terms of their presence at the time of ovarian cancer diagnosis. Information was accessed on comorbidities recorded in the ten preceding years. We then computed the prevalence of comorbidity in study patients diagnosed during each study period (1995–1997, 1998–2000, and 2001–2004).

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Survival

For each comorbidity group (Charlson comorbidity index 0, 1–2, or 3+), we computed Kaplan–Meier survival curves for ovarian cancer patients by period of diagnosis (1995–1997, 1998–2000, and 2001–2004) and estimated survival at 1 and 5 years using the Kaplan–Meier product-limit method(14). Follow-up started on the date of ovarian cancer diagnosis and continued until death, emigration, or January 31, 2005.

To assess the association between comorbidity and relative mortality, we used Cox proportional hazards regression analysis. We computed 1- and 5-year hazard ratios as a measure of mortality rate ratios (MRRs) for each of the three time periods, adjusting for age. Patients with no comorbidity served as the reference group. For the period 2001–2004, it was not possible to compute a 5-year survival or mortality because of the relative short follow-up period. We assessed the assumption of proportional hazards in the Cox model graphically. Estimates were obtained with corresponding 95% confidence intervals (95% CI).

Analyses were performed using SAS version 9.1.3 (SAS Institute Inc., Cary, NC).

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Results

Prevalence of comorbidity

A total of 1995 women were identified who were diagnosed with ovarian cancer between 1995 and 2004. Of these women, 1525 (76%) had no comorbidity recorded, 379 (19%) had comorbidity score 1–2, and 91 (5%) had comorbidity score 3+. The prevalence of patients with no comorbidity decreased from 80% to 75% during the study period. At the same time, the prevalence of the patients with Charlson score 1–2 increased from 16% during the 1995–1999 period to 21% during the 2000–2004 period, and the prevalence of patients with Charlson score 3+ was essentially unchanged (4–5%).

Throughout the study period, the patients' median age remained consistently 63 years. For patients with Charlson scores 0 or 1–2, the median age also did not change substantially over time (from 60 to 59 years and from 72 to 70 years, respectively). In contrast, the median age of patients with Charlson score 3+ increased from 67 years in the 1995–1997 period to 73 years in the 1998–2000 period and then to 68 years in the 2001–2004 period.

The prevalence of the 19 comorbid conditions among women in our study population is shown in Table 1. Comorbidity level by diagnosis period is provided in Table 2.

Table 1
Table 1
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Table 2
Table 2
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Survival

Overall 1-year survival increased from 68% (95% CI, 64–71) in 1995–1997 to 70% (95% CI, 67–74) in 1998–2000 and to 73% (95% CI, 70–76) in 2001–2004. Overall 5-year survival did not change greatly over time: 38% (95% CI, 34–42) survived for 5 years in 1995–1997 compared to 39% (95% CI, 35–42) in 1998–2000.

Figure 1 presents Kaplan–Meier survival curves for women with ovarian cancer and no comorbidity (Charlson score 0) by year of diagnosis. For this group, 1-year survival increased from 71% (95% CI, 67–75) in 1995–1997 to 75% (95% CI, 71–79) in 1998–2000 and to 79% (95% CI, 75–82) in 2001–2004 (Table 3). Five-year survival did not show much change during the study period (Table 3).

Figure 1
Figure 1
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Table 3
Table 3
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Figure 2 presents Kaplan–Meier survival curves for women with ovarian cancer and Charlson score 1–2. One-year survival was 58% (95% CI, 48–67) for women diagnosed in 1995–1997, 59% (95% CI, 50–67) for women diagnosed in 1998–2000, and 58% (95% CI, 49–66) for women diagnosed in 2001–2004 (Table 3). Five-year survival was 28% (95% CI, 19–37) for women diagnosed in 1995–1997 and 30% (95% CI, 22–38) for women diagnosed in 1998–2000 (Table 3).

Figure 2
Figure 2
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Kaplan–Meier survival curves for women with Charlson score 3+ are shown in Figure 3. One-year survival was 46% (95% CI, 26–64) for women diagnosed in 1995–1997, 50% (95% CI, 32–65) for women diagnosed in 1998–2000, and 52% (95% CI, 34–67) for women diagnosed in 2001–2004 (Table 3). Five-year survival was 29% (95% CI, 13–48) for women diagnosed in 1995–1997, decreasing to 18% (95% CI, 7–32) for women diagnosed in 1998–2000 (Table 3).

Figure 3
Figure 3
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Compared with women with Charlson score 0, the 1-year age-adjusted MRR for women with Charlson score 1–2 was 1.1 (95% CI, 0.8–1.6) for those diagnosed with ovarian cancer in 1995–1997, 1.3 (95% CI, 1.0–1.8) for those diagnosed in 1998–2000, and 1.7 (95% CI, 1.3–2.4) for those diagnosed in 2001–2004 (Table 3). The 1-year age-adjusted MRR for women with Charlson score 3+ was 2.4 (95% CI, 1.4–4.3) for those diagnosed with ovarian cancer in 1995–1997, 1.6 (95% CI, 1.0–2.7) for those diagnosed in 1998–2000, and 2.2 (95% CI, 1.3–3.8) for those diagnosed in 2001–2004 (Table 3).

The 5-year age-adjusted MRR for women with Charlson score 1–2 was 1.1 (95% CI, 0.8–1.4) for those diagnosed with ovarian cancer in 1995–1997 and 1.1 (95% CI, 0.8–1.3) for those diagnosed in 1998–2000 (Table 3). Among patients with Charlson score 3+, the 5-year age-adjusted MRRs were 1.7 (95% CI, 1.0–2.7) for those diagnosed in 1995–1997 and 1.6 (95% CI, 1.1–2.3) for those diagnosed in 1998–2000 (Table 3).

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Discussion

In this population-based study, we found that nearly one quarter of all ovarian cancer patients had at least one recorded comorbid condition. The prevalence of comorbidity increased with age, but even after controlling for age, comorbidity remained a negative prognostic factor. The MRR was approximately twice as high in patients with severe comorbidity (3+) compared to those without comorbidity.

The main strengths of our study are its large size, Denmark's uniformly organized health care system allowing a population-based design with complete follow-up, and availability of information for computing the Charlson index.

A study limitation is the possibility of some misclassification of ovarian cancer diagnoses in the HDRs(15). A previous study showed that some misclassification occurs because of the difficulty in separating borderline tumors from invasive ovarian cancer(15). Borderline tumors recorded as benign in the HDRs were not included in the study, while those recorded as malignant were included. Up to 15% of ovarian cancer patients have borderline tumors(16), and these patients are often younger and less affected by comorbidity than patients with invasive cancers. Although age was taken into consideration in the analysis, we cannot rule out the possibility that misclassification of borderline tumors biased the relative estimates away from the null. Still, our findings of a negative impact of comorbidity replicate those of two other studies that did not include any borderline tumors(8,9). O'Malley et al.(8) studied 1051 American women with ovarian cancer FIGO stage IC or higher and found decreased survival associated with comorbidity: the hazard ratio for patients with any comorbid conditions was 1.4 (95% CI, 1.1–1.7) compared to patients with no comorbid conditions. In a German study, Du Bois et al.(9) similarly found that comorbidity was an independent prognostic factor (hazard ratio=1.77 [95% CI, 1.23–2.54]). Similarly, Piccirillo et al.(17) found a negative effect of comorbidity on survival from gynecological cancers, although no separate analysis was conducted for ovarian cancer.

In our study, we chose to use data from HDRs because they are updated daily(15) and include information on comorbidity. In contrast, the Danish Cancer Registry has a high level of completeness but a delay in data availability. It also contains no information on comorbidity.

Another possible study weakness is associated with use of the validated Charlson comorbidity index to determine comorbidity. When it is applied to administrative data, misclassifications of comorbidity may occur(18). As well, this index is known to have a high specificity(5) but a variable degree of sensitivity(19). It is thus possible that some patients with comorbid conditions may have been classified erroneously as having Charlson score 0. However, registration of comorbid conditions may have become more complete over time, so any misclassification would have been greater in earlier periods. This may explain some of the improved survival among those with comorbidity score 0.

No comorbidity was recorded for 76% of the ovarian cancer patients in our sample, which was higher than in a Norwegian study that found an absence of comorbidity in 66% of its sample using the Charlson comorbidity index(20). Compared with the Norwegian study, we found a lower prevalence of patients with an index score of 1–2 (19% vs 32%) and a higher proportion of patients with an index score of 3+ (5% vs 2%)(20). An American and a Dutch study, using different methods for collecting data on comorbidity, found a lower prevalence of ovarian cancer patients without comorbidities than we did (51% and 49%, respectively)(4,6). The American study relied on diagnoses present at the time of ovarian cancer diagnosis, such as cardiovascular disease(4). The Dutch study used a modified Charlson comorbidity index, defining comorbidity as diseases present at the time of cancer diagnosis(6). Different coding schemes may have been used in the various countries, explaining the divergent findings. It is also possible that ovarian cancer may not be consistently diagnosed in all countries among women with severe comorbidity.

Our findings differ from those of DiSilvestro et al.(21), who conducted a small American study with less than one-tenth the number of study participants. They found no association between comorbidity and overall survival in 137 ovarian cancer patients using a modified Charlson comorbidity index(21). In a Dutch study by Maas et al.(6), the analysis was restricted to approximately 500 ovarian cancer patients with FIGO-stages II and III. They used a slightly modified Charlson comorbidity index and concluded that comorbidity did not seem to have a prognostic effect. The impact of comorbidity may well differ according to the stage of the disease(22). Since our study lacked sufficient information on disease stage, we were unable to address this question.

It is important to note that our study lacked information about treatment, an independent prognostic factor for overall survival(23,24). We therefore were unable to evaluate whether different treatment regimens affect the association between comorbidity and survival from ovarian cancer, as has been found for other cancer types(22). Finally, in our study, we examined all-cause mortality but did not address cause-specific mortality. However, all-cause mortality is a robust measure, given the difficulty of distinguishing between the contribution to mortality from the ovarian cancer itself and that from cancer complications or underlying diseases.

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Conclusions

One quarter of ovarian cancer patients had at least one recorded comorbid disease, and 5% had severe comorbidity. Severe comorbidity was a predictor of reduced survival in Danish women with ovarian cancer. Further research is required to determine whether the increased mortality is due to the comorbidity itself or to the possibility that ovarian cancer patients with comorbid conditions receive less aggressive treatment.

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Acknowledgments

This study received support from the Western Danish Research Forum for Health Sciences, the Research Foundation of Northern Jutland, Research Initiative of Aarhus University Hospital, Ebba and Aksel Schølin Foundation, Peder Kristian Tøftings and Dagmar Tøftings Foundation, Heinrich Kopps Foundation, Herta Christensens Foundation, Ingeborg and Leo Dannins Foundation for Scientific Research, Danish Research Agency (Grant 271-05-0511), Karen Elise Jensens Foundation, and the Danish Cancer Society.

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References

1 Parkin DM, Bray F, Ferlay J, Pisani P. Global cancer statistics, 2002. CA Cancer J Clin 2005;55:74–108.

2 Sant M, Aareleid T, Berrino F et al. EUROCARE-3: survival of cancer patients diagnosed 1990–94—results and commentary. Ann Oncol 2003;14(Suppl. 5):v61–118.

3 Janssen-Heijnen ML, Houterman S, Lemmens VE, Louwman MW, Coebergh JW. Age and co-morbidity in cancer patients: a population-based approach. Cancer Treat Res 2005;124:89–107.

4 Sharma S, Driscoll D, Odunsi K, Venkatadri A, Lele S. Safety and efficacy of cytoreductive surgery for epithelial ovarian cancer in elderly and high-risk surgical patients. Am J Obstet Gynecol 2005;193:2077–82.

5 de Groot V, Beckerman H, Lankhorst GJ, Bouter LM. How to measure comorbidity. A critical review of available methods. J Clin Epidemiol 2003;56:221–9.

6 Maas HA, Kruitwagen RF, Lemmens VE, Goey SH, Janssen-Heijnen ML. The influence of age and co-morbidity on treatment and prognosis of ovarian cancer: a population-based study. Gynecol Oncol 2005;97:104–9.

7 Janssen-Heijnen ML, Houterman S, Lemmens VE, Louwman MW, Maas HA, Coebergh JW. Prognostic impact of increasing age and co-morbidity in cancer patients: a population-based approach. Crit Rev Oncol Hematol 2005;55:231–40.

8 O'Malley CD, Cress RD, Campleman SL, Leiserowitz GS. Survival of Californian women with epithelial ovarian cancer, 1994–1996: a population-based study. Gynecol Oncol 2003;91:608–15.

9 Du Bois A, Rochon J, Lamparter C, Pfisterer J. Pattern of care and impact of participation in clinical studies on the outcome in ovarian cancer. Int J Gynecol Cancer 2005;15:183–91.

10 Marx CI, Moller C, Bendixen A, Kehlet H, Ottesen BS. Ovarian cancer in Denmark. Status of the surgical intervention. Ugeskr Laeger 2006;168:1537–40.

11 Frank L. Epidemiology. When an entire country is a cohort. Science 2000;287:2398–9.

12 Andersen TF, Madsen M, Jorgensen J, Mellemkjoer L, Olsen JH. The Danish National Hospital Register. A valuable source of data for modern health sciences. Dan Med Bull 1999;46:263–8.

13 Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987;40:373–83.

14 Rothman KJ. Epidemiology: an introduction. Oxford: Oxford University Press, 2002.

15 Tetsche MS, Nørgaard M, Skriver MV, Andersen ES, Lash TL, Sørensen HT. Accuracy of ovarian cancer ICD-10 diagnosis in a Danish population-based hospital discharge registry. Eur J Gynaecol Oncol 2005;26:266–70.

16 Trimble CL, Trimble EL. Management of epithelial ovarian tumors of low malignant potential. Gynecol Oncol 1994;55:S52–61.

17 Piccirillo JF, Tierney RM, Costas I, Grove L, Spitznagel EL Jr. Prognostic importance of comorbidity in a hospital-based cancer registry. JAMA 2004;291:2441–7.

18 Sørensen HT. Regional administrative health registries as a resource in clinical epidemiology. A study of options, strengths, limitations and data quality provided with example of use. Int J Risk Safety Med 1997;10:1–22.

19 Wilchesky M, Tamblyn RM, Huang A. Validation of diagnostic codes within medical services claims. J Clin Epidemiol 2004;57:131–41.

20 Tingulstad S, Skjeldestad FE, Halvorsen TB, Hagen B. Survival and prognostic factors in patients with ovarian cancer. Obstet Gynecol 2003;101:885–91.

21 DiSilvestro P, Peipert JF, Hogan JW, Granai CO. Prognostic value of clinical variables in ovarian cancer. J Clin Epidemiol 1997;50:501–5.

22 Read WL, Tierney RM, Page NC et al. Differential prognostic impact of comorbidity. J Clin Oncol 2004;22:3099–103.

23 Chan JK, Loizzi V, Lin YG, Osann K, Brewster WR, DiSaia PJ. Stages III and IV invasive epithelial ovarian carcinoma in younger versus older women: what prognostic factors are important? Obstet Gynecol 2003;102:156–61.

24 Brun JL, Feyler A, Chene G, Saurel J, Brun G, Hocke C. Long-term results and prognostic factors in patients with epithelial ovarian cancer. Gynecol Oncol 2000;78:21–7.

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Keywords:

comorbidity; epidemiology; ovarian cancer; prognosis

© 2008 by the International Gynecologic Cancer Society and the European Society of Gynaecological Oncology.

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