2. Methods
The study makes use of data from the statutory health insurance (SHI), which insures approximately 88% of the German population, or approximately 73 million individuals [
2,
3]. The SHI system comprises approximately 96 independent health insurance providers [
4], each offering a comprehensive benefit package as mandated by social law. This setup ensures nearly complete coverage of healthcare costs, with minimal co-payments by patients. The SHI’s payments to healthcare providers account for the majority of the total healthcare costs for individual patients. While the SHI records all reimbursed tests and procedures, it does not have access to clinical data such as lab results or disease severity scores.
The analysis is based on claims data from the Institute for Applied Health Research Berlin GmbH (InGef) research database, which contains a representative sample of approximately 4 million individuals for research purposes, mirroring the German population’s structure in terms of age, gender, and regional distribution. This sample includes data from over 50 health insurances and represents 4.7% of the German population and 5.4% of the SHI-insured population as of 2022 [
3]. The InGef database is regarded as a reliable source of information regarding external validity with regard to morbidity, mortality, and medication usage patterns [
5]. According to the Good Practice of Secondary Data Analysis (GPS), consultation with an ethics committee is not required for analyses based exclusively on secondary data in Germany [
6].
The database monitors the insurance status of nearly 80% of the population for up to six years (2017–2022). It encompasses comprehensive information on healthcare sectors, including patient demographics, inpatients, outpatients, pharmacy services, remedies, devices, and aids, as well as data on the incapacity to work and sick leave payments.
A structured approach was employed to calculate the number of participants in clinical trials for systemic lupus erythematosus (SLE) and chronic lymphocytic leukemia (CLL) within Germany. Both diseases are distinctly classified according to the ICD-10-GM and represent the oncology and chronic disease trial situations, respectively. Furthermore, indications were selected based on the availability of clinical trials in Germany, the innovative treatment landscape to potentially reflect changes in treatment pathways, and the availability of scientific experts and patient associations in the respective indications in Germany.
The methodology employed involved adapting the research timeframe to align with the data available in the InGef database, which spanned from 2017 to 2022. The focus was on clinical trials conducted in Germany for the respective indications of SLE and CLL, specifically those that commenced and concluded patient enrolment during this period. To identify the population, the relevant inclusion and exclusion criteria from clinical trials for SLE and CLL patients conducted in Germany during the specified time period were extracted from CT.gov. These criteria were then applied to the InGef data pool of patients diagnosed with SLE or CLL from 2017 to 2022. This enabled the identification of a subset of patients who met the criteria for potential participation in the trials.
To identify SLE patients potentially eligible for clinical trials, the following inclusion criteria were applied: 1. patients with an ICD-10-GM diagnosis for SLE (M32.-) in the inpatient sector (primary or secondary discharge date diagnosis) and/or at least two different quarters (M2Q criterion) in the outpatient sector (verified diagnosis); 2. patients aged at least 18 years; 3. patients without diagnosis codes indicating pregnancy or breastfeeding; 4. patients prescribed at least one background medication (selected corticosteroids, immunosuppressants or immunomodulatory agents, anti-malarials, NSAIDs) identified by ATC or OPS codes; and 5. patients without chronic infections.
CLL patients potentially eligible for clinical trials were identified based on the following inclusion criteria: 1. patients with at least one ICD-10-GM diagnosis code for CLL (C91.1.-) in the inpatient sector (primary or secondary discharge date diagnosis) and/or at least two in different quarters (M2Q criterion) in the outpatient sector (verified diagnosis); 2. patients aged at least 18 years; 3. patients with relapsed/refractory (RR) CLL, defined as at least one prescription for RR disease recommended for follow-up treatment identified by ATC and OPS codes (selected protein kinase inhibitors, monoclonal antibodies and antibody drug conjugates, other antineoplastic agents licensed for first-line treatment); 4. patients without a diagnosis code indicating transformation of CLL; and 5. patients without malignancies other than CLL.
All results from the InGef research database were extrapolated to the German population based on the underlying analysis sample in the InGef research database and the German population according to the data of the Federal Office of Statistics (DESTATIS) for the year 2022 [
2].
Furthermore, we sought to validate our calculated numbers by comparing them with data from publicly available sources. This included a comparison of the planned number of clinical trial participants listed on PharmNet.Bund with the actual patient numbers recorded in EU CTR [
7,
8].
Aiming for an increased robustness of our study and to ensure the validity of our findings, we integrated a qualitative research component in the form of expert interviews, employing techniques to enhance the robustness of the interviews. In order to achieve a high level of reliability, it is essential to utilize a structured format comprising a pre-defined set of open-ended questions, trained interviewers, and the implementation of consistency checks. These practices help to ensure that expert interviews yield reliable and valid data, thereby making them a robust method for qualitative research. These interviews were conducted with scientific experts and patient experts (patient advocacy groups—PAGs) with a particular focus on SLE and CLL. Additionally, interviews were conducted with experts across various medical specialties (obesity, cardiovascular diseases) to gain a broader perspective and more generalized insights.
Firstly, nine scientific experts were identified and engaged with (three in SLE, three in CLL, two in obesity, and one in cardiovascular diseases), each of whom are recognized experts in their respective fields. The selection process was based on a review of relevant stakeholders in the respective indications, who were identified as contributing to national guidelines or having a high number of publications related to the indication. A total of 110 stakeholders were invited to participate, and nine scientific experts expressed willingness to take part. In addition, we consulted with three patient advocacy groups, one representing individuals with SLE and two for cystic fibrosis. These consultations were deemed relevant due to significant changes based on innovations in the treatment environment. Despite efforts to engage with patient advocacy groups also representing CLL, no other group was participating. Furthermore, consultations were held with the clinical research organizations, and the study coordinating association in Germany and two industry experts specialized in the development of clinical trials. The objective was to obtain insights that would not only validate our quantitative data but also provide a deeper understanding of the real-world implications of our findings.
Secondly, the interviews were structured to cover a range of topics pertinent to SLE and CLL treatment and research. These included discussions on current challenges in clinical trials and the potential impact of clinical trials on standard treatment protocols. The insights from these interviews were then analyzed and synthesized.
4. Discussion
In summary, our findings indicate an unexploited potential to enroll patients with chronic diseases compared to the relatively higher enrolment rates observed for oncology diseases, such as CLL.
The majority of SLE patients (84.6%) were treated in accordance with German treatment guidelines. The discussions with SLE experts supported the number of patients receiving SLE-related treatments versus those receiving no SLE-related treatments identified in the German claims database. The experts indicated that the patients receiving no SLE-related treatment are most likely to have mild symptoms and do not require any treatment [
13]. However, from a gold standard perspective, the percentage of hydroxychloroquine should be up to 80%, taking adverse events into consideration. The utilization of biologics is perceived by scientific experts to be below the number of patients requiring them, also based on the EULAR recommendations for the management of SLE [
10]. An evaluation of the claims data based on the EULAR treatment recommendations also indicates a higher need for biologics, with approximately 14% of SLE patients having moderate to severe symptoms in 2022 (potentially double counting due to the treatment recommendations). Both figures indicate, according to the interviewed experts, that the prescription behavior in Germany is more reserved regarding biologics and that new therapy options might not be sufficiently adopted.
A significant proportion of patients with an ICD-10-GM code for CLL was observed to not receive any CLL-related therapy (78.0%), while 11.9% received a treatment in accordance with German guidelines and 10.2% received antineoplastic agents, although they were not up to date with current guideline recommendations. The high percentage of non-CLL treated patients is attributed by experts to the high percentage of patients with CLL being either in remission or not requiring any treatment due to a mild course of the disease. The total number of CLL-prevalent patients was perceived to be underreported due to a well-known discrepancy between reality and claims data, which is attributed to a lag in the identification and diagnosis of the disease [
14,
15,
16]. Further limitations can be attributed to the lack of clinical data and the absence of disease and patient-related characteristics in the claims database [
17]. The number of individuals in the eligible population may be subject to some uncertainty due to the inclusion of additional characteristics in clinical trials. Also, the anonymization of data is a crucial step in ensuring the privacy of individuals. However, this process inevitably restricts access to detailed person-level data, which may in turn limit the depth of certain analyses [
17]. Finally, it is important to note that claims data are primarily collected for reimbursement purposes, not for epidemiological research. Consequently, the database captures only those patients who sought medical care and received a diagnosis that triggered reimbursement. Undiagnosed cases or those managed without the formal documentation of an ICD-10-GM code were not included in our analysis. Furthermore, it may overrepresent more severe cases requiring medical attention while underrepresenting milder or asymptomatic infections that did not prompt a physician visit.
The findings indicate that patients with chronic diseases, such as severe SLE, show lower enrollment rates than patients suffering from cancer, such as CLL. Hence, specifically for chronic and non-oncological conditions, there may be a greater and untapped potential for widening participation in clinical studies. A comparison of potential and actual patients eligible for clinical trials indicates that SLE patients in Germany are less likely to participate in clinical trials and the clinical infrastructure (i.e., specialized centers for rheumatology or dermatology) might be less mature than those with CLL. This suggests that there is a need to increase participation to potentially improve patient outcomes. According to experts in clinical trial design based on the qualitative evaluation, an inclusion of 10 to 20% of the total eligible population is a realistic threshold to consider in clinical trial planning. It is important to consider the number of eligible patients with caution, as an additional step of excluding patients receiving no treatment most likely due to the course of the disease (14.5%) is necessary in this funnel. This was based on expert recommendations, as these patients would not participate in clinical trials. For SLE, the planned number of patients to be included in a clinical trial was within this threshold of eligible patients. However, the actual number of patients enrolled in the clinical trial was significantly lower. According to experts, this is due to a lack of information provided to patients about potential treatment alternatives in clinical trials, as well as to community physicians and specialists.
The number of planned patients to be enrolled in the CLL clinical trial met the threshold of 10 to 20% of the eligible population. It was anticipated that almost all planned patients for Germany would be included in the clinical trial.
Expert interviews are a valuable source of in-depth insights into clinical practice. However, they are not without limitations. These include the potential for selection bias among experts and the possibility of personal biases influencing the responses of the experts. Additionally, findings may not be easily generalizable. The presence and behavior of the interviewer can also influence responses, introducing further bias. More research should be conducted to understand individual patient factors, such as patient willingness, economic conditions, and psychological or social factors. A non-life-threatening condition impacts therapeutic need and highlights the remaining hurdles in German clinical trials and the barriers to providing access to innovative treatments for patients with chronic widespread diseases. Germany has still a large untapped potential to enroll patients in clinical trials and to make innovative treatments available to patients in need. Finally, more research on the root causes is desirable in order to devise measures that could lead to patient organizations and healthcare professionals informing patients (incl. those with non-oncological chronic conditions) to be proactive in seizing the opportunity to participate in clinical research.