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EJSO 36 (2010) 496e500
Postresection survival outcomes of pancreatic cancer according to demographic factors and socio-economic status Y. Kuhn, A. Koscielny, T. Glowka, A. Hirner, J.C. Kalff, J. Standop* Department of Surgery, University of Bonn Medical Center, Sigmund-Freud-Strasse 25, D-53105 Bonn, Germany Accepted 17 August 2009 Available online 12 September 2009
Abstract Aim: Aim of the study was to evaluate the impact of demographic factors (DGF) and socio-economic status (SES) on survival after pancreatic cancer resection in a German setting. Methods: Patients with pancreatic adenocarcinoma and pancreaticoduodenectomy were identified from our pancreatic resection database (1989e2008). DGF, SES, survival and tumor-related information were obtained from hospital records, a registry office questionnaire, and telephone interviews with patients, relatives and general practitioners. Results: Follow-up was completed in 117 patients. Median overall survival and 5-year survival rate was 22 month and 10%, respectively. Survival significantly improved over time with a 16% 5-year survival and a median survival of 27 month for recent patients. The longest survival period with a median of 63 month was observed for patients with AJCC stage I. Tumor-related factors and treatment period, but not SES influenced survival after pancreatic cancer resection in our cohort. Conclusions: To our knowledge, this is the first study to explore survival from pancreatic cancer according to DGF and SES in a German setting. Disparities in survival among our patients depend solely on tumor-related factors and treatment period and could not be explained by SES including key factors like income or type of health insurance. The comparable postresection outcome of patients with low and high SES at our department could be in part due to the universal German multi-payer health system, based on compulsory enrolment for the majority, which seems not to support health care inequalities seen in other OECD countries. Ó 2009 Elsevier Ltd. All rights reserved. Keywords: Pancreatic cancer; Resection; Survival; Demographic factors; Socio-economic status; Income level; Health insurance status
Introduction Epidemiologists have for a long time recognized the importance of social inequalities in shaping the patterns of morbidity and mortality.1 Especially in the U.S., recent studies have documented increasing disparities in death rates by socio-economic status (SES) for a variety of benign and malignant diseases.2e4 A recent study from New England, for example, showed that a higher SES is significantly associated with improved overall survival following pancreatic cancer resection,5 thereby indicating a relationship between SES and the quality of care Abbreviations: AJCC, American Joint Committee on Cancer; ISCED, International Standard Classification of Education; DGF, Demographic factors; SES, Socio-economic status. * Corresponding author. Tel.: þ49 (228) 287 15109; fax: þ49 (228) 287 14856. E-mail address: [email protected]
(J. Standop). 0748-7983/$ - see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.ejso.2009.08.006
delivered and outcomes. One of the largest populationbased studies on pancreatic cancer survival, conducted in California, showed that poorer patients were less likely to undergo resection and less likely to survive this malignancy and that median survival increased with SES.6 Accordingly, Zell et al. reported a poorer pancreatic cancer survival for underprivileged minorities with lower SES due to treatment differences.7 Bearing in mind the strong national commitment to eliminate health disparities in Germany, purpose of the current study was to evaluate whether survival of patients who underwent resection for pancreatic cancer at our department was also determined by SES including key factors like income level and insurance status. Patients and methods This case series was composed of patients with pancreatic adenocarcinoma who underwent pancreatoduodenectomy
Y. Kuhn et al. / EJSO 36 (2010) 496e500
with curative intent (e.g., no distant metastases, no substantial retroperitoneal or arterial infiltration) between 1989 and 2008 at the Department of Surgery, University of Bonn Medical Center, Germany. Information on survival, DGF, SES, and patients’ and tumor characteristics (Table 1) was obtained from our pancreatic resection database, hospital records, a registry office questionnaire, and by telephone interviews with patients, close relatives and general practitioners. Tumor staging followed the 6th edition of the American Joint Committee on Cancer (AJCC) Cancer Staging Manual.8 SES surrogates Data were collected for individual patients and are not based on the postcode of residence or census data. The cut-off income of V1500 roughly doubles the relative poverty threshold in Germany for a single person, since the majority of our patients were retired and living in a two person household. Further surrogate parameters used in this study that have shown a good correlation with income and are accepted in the literature were education level including university graduation, employment status and type of health insurance and migration background. Assessment of education level was based on the UNESCO’s ‘‘International Standard Classification of Education’’ (ISCED)a. Level 2 refers to secondary modern school (Hauptschule); level 3 comprises junior high school (Realschule) and high school (Gymnasium, Abitur) careers. Statistical analysis Survival analysis was performed by Kaplan-Meier survival estimates and differences between survival curves were assessed by means of the log rank test (SPSS Statistical Software 15, Chicago, Illinois, USA). Nineteen factors were included in a univariate analysis. Multivariate stepwise regression survival analyses using the Cox proportional hazard model were performed for variables with univariate significance, and additionally for variables related to DGF, histopathological factors or SES. p < 0.05 was considered statistically significant. Results Follow-up was completed in 117 patients with a median age of 65 years (range: 41e83). Overall median survival (including all patients with in-hospital mortality) was 22 month, with a 10% 5-year survival rate. Median survivals according to DGF, tumor characteristics and SES as well as statistical results are summarized in Table 1. a
Postresection survival outcomes by demographic factors There were no significant differences in survival based on gender, age or martial status. Fifty-eight patients had a positive smoking history and lost nine month of survival time compared to non-smokers. However, nicotine abuse was not independently prognostic. Living remote from our hospital (>50 km) or in smaller cities (<250,000 residents) was not associated with survival. Over time, the number of patients undergoing curative resection at our department increased. Treatment period was a highly significant prognostic determinant. Of the patients treated between 2000 and 2008, median survival was 27 month and 5-year survival rate 16%. This is significantly better than for patients who were resected in the earlier period (Fig. 1). Postresection survival outcomes by histopathologic factors AJCC stage and tumor differentiation were predictors of survival by multivariate analysis. The longest survival period with a median of 63 month was observed for patients with AJCC stage I (T1eT2, N0, M0). Lymph node status and tumor size in the resected specimen were significant prognostic variables by univariate analysis, but were not independently prognostic. Postresection survival outcomes by socio-economic status There were no significant differences in survival based on any of the surrogate parameters for SES. Almost identical postresection Kaplan-Meier survival curves by income are shown in Fig. 2. Discussion Socio-economic differences in health care have been reported to be substantial and persistent. Many studies indicated a significant association between low SES and poorer cancer survival in Western countries, Australasia and Japan,9e14 while the contribution of specific causes to differences in mortality has been found to vary between countries. In recent years, at least three studies from the U.S. reported a poorer survival of pancreatic cancer among patients with a low SES.5e7 Lim and colleagues even noted that being a pancreatic cancer patient of low SES may be as important a determinant of survival as poor biology or a bad surgery.5 As the elimination of inequalities in population health is a primary goal of health politics, the WHO recently established the Global Commission on Social Determinants of Health.15
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Table 1 Postresection median survivals according to demographic factors, tumor characteristics and socio-economic status.
Demographic factors (DGF)
Socio-economic status (SES)
Gender Age Distance to residence Home town population Martial status Smoking Year
m/w <75/75 <50 km/50 km <250.000/250.000 single/married yes/no 1989e99/2000e08
60/57 104/13 84/31 80/35 41/75 58/49 43/73
20/23 22/12 19/20 19/20 19/23 19/28 14/27
p < 0.01
p < 0.01
AJCC stage T-stage Lymph node Grading Resection status Tumor size
I/II þ III I þ II/III þ IV N0/N1 G I þ II/GIII R0/Rþ <3 cm/3 cm
7/108 18/98 29/88 55/58 69/42 47/64
63/19 29/19 33/19 28/15 21/15 19/14
p < 0.01
p < 0.05 p < 0.01
Income Education level (ISCED) University degree Employment status Health insurance Migration background
<1.500V/1.500V 3/2 yes/no unemployed/employeda state health/private no/yes
38/32 38/53 18/74 4/92 87/30 113/4
25/23 26/20 20/22 15/21 23/17 22/16
p < 0.05 p < 0.01
p < 0.01
p < 0.01
Analyses with no stated p-value were not significant. AJCC Stage: I: T1eT2, N0, M0; II: T3, N0, M0 and T1eT3, N1, M0; III: T4, N0eN1, M0. ISCED: International Standard Classification of Education. a ‘‘Employed’’ includes senior citizens with a positive employment history and housewifes or homemakers.
Explanations by epidemiologists for socio-economic gradients in health have traditionally focused on access to resources, physical exposures in the living and working environment, and health related behaviors.15 In this context, a study comparing health systems in the U.S., Canada and Germany showed that Germans had the easiest access to and least out of pocket expenditure for their health plans. The study also indicated that of the three countries, overall access to medical care is least satisfactory in the U.S.16 In particular, U.S. citizens reported greater likelihood of financially based access problems. However, due to unlimited access to every resident in the German health system e regardless of health insurance status e this is unlikely to be the case with our patients. More recent studies also reported a significant correlation of poorer cancer survival with lower SES due to treatment differences.7 Accordingly, in the present study, we approached the matter of health disparities from a practical point of view, focusing on surgical cancer treatment outcome depending on DGF and SES. Surrogates for SES and role of DGF Epidemiologic studies examining the influence of DGF and SES on cancer frequently use area- or population-based measures as surrogate, usually based on the postcode of residence and census data.5,6,11,17,18 Therefore, these data are imperfect proxy measures of individual levels of SES. To
accurately test this association, data on SES and DGF should ideally be collected for individual patients,19 as was done in our study. The selected socio-economic factors, especially income, education level and health insurance type, have been proven to fairly well correlate with health disparities.20 According to many epidemiological studies, income appears to be one of the best evaluated and most feasible parameter for measuring SES.1 Classification of education level followed ISCED definition to enable an international comparison of the data. Nevertheless, none of these socio-economic factors was shown to correlate with a negative treatment outcome in our cohort. The comparable outcome of patients with private and state or 1.0
Health care systems compared
0.6 <2000 >2000 0.4
Figure 1. Kaplan-Meier survival curve for patients treated between 1989 and 1999 and between 2000 and 2008.
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therefore one of the reasons explaining the significantly better outcome of the latter cohort. As published earlier, this improved success for patients treated in 2000 and thereafter is further attributed to increased experience with the procedure, significant decrease in procedure-related mortality, advances in perioperative care and complication management.26
< 1.500€ > 1.500€ 0.4
Health care in Germany 0.2
statutory health insurance is an important finding, as other studies have shown that diagnoses, treatments, and quality of care all vary according to coverage and type of health insurance.21 Moreover, with the increasing problem of health care funding there is an ongoing and emotionally conducted discussion about privileged care for privately insured patients in Germany. The demographic factors of distance to hospital and number of home town population were chosen to identify additional impediments to health care access including aspects such as lack of easily available specialist and proximate providers or difficulties in transportation. As with socio-economic factors, none of these potentially systemic barriers had any affect on the postresection outcome, indicating a balanced and comprehensive coverage even in rural areas.
The fact that, unlike in many other studies, SES is not a determinant of treatment outcome in our patients could be due to our treatment algorithms but might also be rooted in differences of health care systems. Although expenditure on health is highest in the U.S., highly specialized medical care is available only to a financially powerful proportion of the population. In comparison, Germany, which in 1883 became the first country in the world to mandate health insurance,27 ranks only 4th (11% of GDP) regarding health care expenditure,28 but grants health care access to every citizen. Germany has a universal multi-payer system with two main types of health insurance: ‘‘statutory health insurance’’ (Gesetzliche Krankenversicherung) known as sickness funds and ‘‘private health insurance’’ (Private Krankenversicherung). Compulsory insurance, provided at common rates to all members, applies to those below a set income level and is paid for with joint employereemployee contributions.27 The sickness funds are mandated to provide a wide range of coverage and cannot refuse membership or otherwise discriminate on an actuarial basis. Social welfare health funds protect individual needy families against additional health expenses and disease-related impoverishment.
Survival of pancreatic cancer
There is a wide range of the reported median survival and proportion of 5-year survivors following pancreatic cancer resection. Reports from high-volume institutions are usually better and sometimes exceed average data by far.22,23 One area of concern is the difference between actual and actuarial survival, with the latter leading to an overestimation of survival in some cases. Another concern is the inclusion of cases that may not actually be true pancreatic adenocarcinoma. We included only cases according to the diagnosis stated on the pathology report, but did not once again review the pathology specimens for this study. Nevertheless, an unintentional and probably negligible overestimation should be uniformly distributed among the statistically evaluated groups. The role of postoperative chemotherapy as a powerful predictor of improved survival following pancreatic cancer resection was a consistent finding in many published studies 5,7,24,25 and was therefore not once again addressed in this work. Nevertheless, adjuvant chemotherapy for resected pancreatic cancer has been on offer to every suitable patient since 2003 and is
This study provides a detailed analysis of the potential effects of SES and DGF on the outcome of pancreatic cancer in a German university hospital. Tumor-biologic characteristics and treatment period remain the most import predictors of survival. SES was not a determinant of health related disparities after pancreatic cancer resection. In our patients, environmental conditions and personal behaviors as well as psychosocial influences in terms of, e.g., stress or depression might also play an important and likely larger role in determining treatment outcome.
Figure 2. Kaplan-Meier survival curve according to monthly income. Cutoff earning was V1,500/month.
Conflict of interest None of the authors has any financial and personal relationships with other people or organisations that could inappropriately influence (bias) the work. There are no potential conflicts of interest including employment, consultancies, stock ownership, honoraria, paid expert testimony, patent applications/registrations, and grants or other funding.
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