The WiZen study
WiZen is a cohort study based on German routine health insurance data provided by the AOK Research Institute (Wissenschaftliches Institut der AOK, WIdO) and data provided by the cancer registries Dresden, Erfurt, and Regensburg. The main objective of the study is to compare German certified cancer centers and non-certified hospitals regarding patient survival. The study addresses breast cancer, colorectal cancer, gynecological cancer, head and neck cancer, lung cancer, neurooncological tumors, pancreatic cancer, and prostate cancer. Here, we report results for pancreatic cancer based on health insurance data.
The WiZen study combines medical expertise with profound data analysis targeted at health insurance and cancer registry data. Clinical experts contribute to case and variable definitions, selection and definition of outcomes, relevant risk factors, and treatments, and interpretation and discussion of empirical findings. Methodological expertise and experience in preparation and modeling of health insurance data is provided by the Center for Evidence-Based Healthcare (Zentrum für evidenzbasierte Gesundheitsversorgung, ZEGV).
Patient characteristics were derived from AOK health insurance data, covering the period 2006–2017. The data included oncological and non-oncological inpatient and outpatient diagnoses (codes according to International Statistical Classification of Diseases—German Modification; ICD-10-GM), treatments and medical procedures in terms of OPS codes (German adaption of ICMP) and EBM (Einheitlicher Berwertungsmaßstab, the German outpatient procedure coding system), ATC codes (medical prescriptions), dates of hospital admissions and discharges, demographic characteristics (age, sex), insurance status, and date of death. A patient was considered as incident in the period 2009–2017 only if there was no diagnosis of pancreatic cancer in 2006–2008.
We used data on hospital characteristics from the German Standardized Quality Reports (SQR, German: Standardisierte Qualitätsberichte). Publishing these reports is mandatory for all German hospitals. For each calendar year in the data set, we used most recent information from SQR data (2010, 2012, 2014, or 2016). Finally, the GCS provided information on GCS-certified cancer centers, including the exact date of certification.
Data protection and ethics
Data on GCS certification, patient and hospital characteristics included in hospital insurance data were pseudonymized at WIdO. Pseudonymized data were analyzed at ZEGV. The WiZen study was approved by the ethics committee of the TU Dresden (approval number: EK95022019). The study was registered at ClinicalTrials.gov (identifier: NCT04334239). Data processing and analyses was conducted in line with the General Data Protection Regulation of the European Union.
Inclusion and exclusion criteria
From the cohort of patients with the first diagnosis of pancreatic cancer (ICD-10-GM: C25) in 2009–2017 we excluded those who a) were not covered by AOK insurance over the entire observation period, b) had no inpatient primary diagnosis of pancreatic cancer, c) were younger than 18 years of age at date of diagnosis, d) died at date of diagnosis, and if e) there were missing hospital characteristics of the treating hospital. In addition, we excluded patients if they f) were treated in a hospital which became a GCS-certified center within 1 year subsequent to treatment as these hospitals are likely to have already established structures required for certification prior to certificate issue, which would introduce potential misclassification bias. A detailed description of all reasons for exclusion is provided in the Additional file 1.
Primary outcome was all-cause mortality. Follow-up for each included patient started at the date of index treatment and ended at date of death or the end of the observation period (December 31,2017), respectively. Index treatment was defined as the first entity-specific inpatient treatment documented in combination with primary ICD-10-GM diagnosis C25. We considered dates of death until December 31, 2017 and treated all other patients as right-censored at this date using the complete approach . Survival time was expressed in years in all statistical analyses.
Treatment in certified cancer center
The GCS certifies German cancer centers fulfill pre-specified criteria (e.g. adherence to relevant clinical guidelines, minimum number of treated patients per year) . Currently (August 2021), there are 120 GCS-certified pancreatic cancer centers , which belong to the group of visceral oncology centers. Since the (quality of) primary resection has relevant influence on survival prospects, we considered a patient to have received treatment in a GCS-certified cancer center if primary tumor resection, as indicated by entity-specific OPS-codes (5–601, 5–602.y, 5–604) in the presence of primary diagnosis C25, was conducted in a GCS-certified pancreatic cancer center. In case of no documented primary resection, we used the first inpatient treatment with primary diagnosis C25 to determine whether the patient was treated in a GCS-certified pancreatic cancer center.
For hospitals that form an association, no 1:1 merge with data on certification was possible. We considered patients who were treated in a hospital belonging to an association to have received center treatment if at least one of the hospitals belonging to that association was GCS-certified. The rationales for this decision were that 1) there may be spill-over of expertise between certified and non-certified hospitals forming an association and 2) treating non-certified hospitals as certified results in a rather conservative estimation of the certification effect, implying that the true effect may be larger in absolute terms. In addition, we stratified single hospitals and hospitals forming an association for sensitivity analysis.
At the patient level, we adjusted for age at index treatment, sex, the presence of distant metastases (ICD-10-GM: C78-C79) and other oncological diseases prior to/at first diagnosis of pancreatic cancer, and 17 Elixhauser comorbidities  selected by clinical experts in the study team (a detailed description of covariates is provided in the Additional file 1, Table S1). Elixhauser comorbidities were included as separate, binary covariates. At the hospital level, we used data on the number of hospitals beds, university hospital status, teaching hospital status, and hospital ownership (public/non-profit/private). In addition, we included dummies for the calendar year of index treatment in all model specifications. These dummies capture potential effects of medical progress and imperfect washout at beginning of the observation period.
We described patient and hospital characteristics by median and first/third quartile (Q1/Q3) in case of continuous variables and absolute and relative frequencies in case of categorical variables. Analysis of patient survival is subject to multiple methodological challenges [26, 27]. Accordingly, multiple methodological approaches for survival analysis have been proposed . To estimate differences in unadjusted survival between GCS-certified pancreatic cancer centers and non-certified hospitals in the first five years after index treatment, we applied the Kaplan–Meier estimator as a well-established, non-parametric method . We adjusted differences in total patient survival between GCS-certified pancreatic cancer centers and non-certified hospitals for patient and hospital characteristics using Cox regression with shared frailty . Covariates were included in the Cox models to get as close as possible to the cause-specific survival rate despite the non-randomized study design. Compared with fully parametric survival models, the Cox regression model offers the advantage that the baseline hazard does not have to be specified for consistent estimation of the model coefficients . Our large sample including more than 45,000 patients provided a sound basis for exploiting this statistical property of consistency. By including a random intercept at the hospital level, the Cox model with shared frailty accounted for correlation between outcomes of patients treated in the same hospital .
For sensitivity analysis, we estimated separate Cox models for specific patient and hospital groups (sex (male/female), other oncological disease (yes/no), single hospital/association, distant metastasis (yes/no), resection (yes/no), number of hospital beds (< 500, > = 500)). In addition, we explored differences between GCS-certified pancreatic cancer centers according to continuity of certification. To assess the robustness of our results regarding alternative definitions of survival time, we replaced survival since index treatment by survival since first diagnosis for further sensitivity analysis. Furthermore, we censored the survival of all patients one year after index treatment to explore the sensitivity of our results regarding length of follow up. Finally, we excluded patients with incident pancreatic cancer in the most recent data year (2017). The rationale for this analysis was that information on patients’ dates of death included in our data may be less complete in more recent data years due to delays in reporting of deaths to the health insurance. Excluding the most recent data year mitigates the influence of such potentially incomplete information on our findings.