Follicular lymphoma or diffuse large B-cell lymphoma: a population based analysis of epidemiological and health economic aspects in Germany

doi:10.21203/rs.3.rs-4830530/v1

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Follicular lymphoma or diffuse large B-cell lymphoma: a population based analysis of epidemiological and health economic aspects in Germany

https://doi.org/10.21203/rs.3.rs-4830530/v1

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Epidemiological data and information on resource consumption, costs and clinical outcomes of the care of patients (pts) with follicular lymphoma (FL) or diffuse large b-cell lymphoma (DLBCL) in Germany are rare. Objective of this study was to generate information filling these evidence gaps. This retrospective cohort study (2015–2020) is based on anonymized, longitudinal health claims data. Subgroup analyses on pts with stem-cell transplant (SCT) were performed. About n = 950 annual prevalent FL-pts and n = 1.360 DLBCL-pts were analysed per year. Mean age of FL-pts was 67 years (SD ± 13), 50,7%-females. In the DLBCL-cohort mean age was 68,6 years (SD ± 13,6), 44,4%-females. The share of “agranulocytosis and neutropenia” as an example of the analyzed side effects was: FL 7,2% and DLBCL 16%. Of the FL-pts 64% had min. one hospital admission, with mean 2 admissions (SD ± 2,3) and a mean duration of 21 days (SD ± 44,7) per year. In the DLBCL-cohort 78% had a hospitalization with 2,9 admissions (SD ± 3,1) and 29 inpatient days (SD ± 47,5). Mean annual costs: FL €15.258 per-patient (SD ± 20.367) and DLBCL €23.455 (SD ± 32.892) per-patient. Mean 12-month costs after autologous-SCT were: FL €46.270 (SD ± 21.936) and DLBCL €56.558 (SD ± 45.926); for allogeneic-SCT (only DLBCL-cohort): €161.662 (SD ± 75.266). This study demonstrate a high burden associated with malignant lymphomas. A considerable number or side effects is documented, indicating a difference between the entities. Length of inpatient stay is stressful for patients and associated with significant costs. Total spending for r/r-pts who require intensive treatments like SCTs are significant. Future efforts including linkage to additional data sources with complementary clinical-information are needed.

Hematological malignancies include a heterogeneous group of lymphomas, multiple myeloma, and leukemia [1]. They differ according to cell type, clinical and molecular characteristics as well as prognosis and treatment options [2, 3]. Follicular- (FL) and diffuse large B-cell lymphomas (DLBCL) are the most common subtypes of malignant lymphomas (ML) [4, 5]. Both entities arise from B-cells and occur with varying aggressiveness and heterogeneity. While in DLBCL, the treatment aim is mostly curative the relative five-year survival of FL patients is also close to 70% due to the indolent course of the disease [6]. On the other hand, watch and wait is an established approach in FL whereas DLBCL progress rapidly without treatment.

Cure rates of approx. 60–80% for DLBCL patients have been published for DLBCL first-line therapy [7, 8]. In contrast, there is no curative setting for FL patients, the overall treatment-aim is long-term remission [2, 9]. International publications show significantly reduced survival rates for patients with relapsed or refractory disease (r/r) in both entities [7, 10–14].

Therefore, a wide variety of treatment concepts are applied to treat these patients, depending on age, general condition, response rate, timing, and other clinical indicators [15]. A various number of chemo-regimes, immunotherapies, radiotherapies, stem cell transplantations (SCT) and also targeted options are recommended by the national FL and DLBCL guidelines [16, 17]. In the last years, innovative therapies for r/r patients have been approved by the EMA e.g. bispecific antibodies or CAR-T-cell therapies [11, 18, 19]. Beside the clinical aspects and benefits, the economic consequences of these novel treatment options on third party payers are not entirely known. Recently, a first Budget-Impact analysis based on inpatient data, estimates a €39M to €166M impact on payers budget of implementing CAR-T-cell therapy in Germany [20].

Especially, both the standard of care and innovative treatments require comprehensive inpatient & outpatient data on e.g. patient characteristics, treatment patterns, resource use, costs and outcomes for all comparators. Comprehensive trans-sectoral longitudinal information on FL- and DLBCL-patients treatment journeys, treatment patterns and resource consumption are still lacking. This evidence gap is challenging for value demonstration, decision-making and development of future care models for responsible stakeholders. This analysis was conducted to partially address this evidence gap, by generating additional information on FL and DLBCL-care in Germany.

STUDY DESIGN

This analysis was a retrospective cohort study based on the InGef research database. The observation period covers the years from 2014 to 2020. Depending on the respective research questions, individual analyses were conducted in the design of a cross-sectional analysis (e.g. incidence and prevalence) and individual analyses in the design of a longitudinal analysis (e.g. the follow-up of stem cell transplanted patients). In the cross-sectional part, prevalent patients were analysed per year. For the determination of the incidence, a prior diagnosis-free pre-observation period of one-year was taken into account. Consequently, the year 2014 was only used as the pre-observation period for the analysis year 2015. Further variables such as demographic and clinical patient characteristics, diagnostic methods, medical therapy, procedures, adverse events, resource utilization, costs, and mortality were considered separately for prevalent patients of both entities.

DATA SOURCE

The InGef database contains anonymized, longitudinal statutory health insurance (SHI) data of about 9 million individuals who are insured by one of more than 50 German health insurance companies included in this database. For this analysis, an annual representative sample of about 3.25 million insured adult persons was used, which is representative to the age and sex distribution of the German population. [21] The total observation period available is limited to six years.

The InGef research database contains socio-demographic information such as gender, age and region of residence. In addition, detailed information on inpatient and outpatient care are obtained from the database. The inpatient data include the date of admission, the date of discharge, diagnostic and therapeutic information (OPS-Level) with exact dates and diagnoses. The outpatient data also contain diagnostic and therapeutic information. Outpatient prescription data contain information (type and quantities) on the ATC-Level. All diagnoses are coded according to the German Modification of the International Classification of Diseases, 10th Revision (ICD-10-GM).

Since all insured individual data in the InGef database are made anonymized and are no longer social data in the sense of § 67 para. 2 SGB X in combination with Art. 4 No. 1 DSGVO, their use for scientific research purposes is compliant with German laws, accordingly no further permission from an ethics committee is required. The analysis follows the recommendations of Good Epidemiological Practice (GEP) and Good Practice Secondary Data Analysis (GPS).

Case definition

Follicular lymphoma (ICD-10: C82.0 – C82.3) and DLBCL (ICD-10: C83.3) diagnosis as an inpatient main or secondary diagnosis and/or two outpatient diagnoses in different quarters of the respective analysis year (M2Q criterion).

For incidence patients, the index date was defined according to the setting of the initial diagnosis: For inpatient main or secondary diagnoses, the date of hospital discharge; for confirmed outpatient diagnoses (with corresponding fulfilment of the M2Q criterion), the first physician contact with the diagnosing physician representing the index date. If an initial outpatient diagnosis was followed by an inpatient diagnosis in another quarter, the outpatient diagnosis defines the index date. If there was an outpatient and an inpatient diagnosis in the same quarter, the date of the inpatient diagnosis was defined as the index date.

Study variables

Patient characteristics were assessed according to the individual index year during the observation period. Sociodemographic variables included age and gender. The Elixhauser- and Charlson Comorbidity Scores were used to describe the general comorbidity burden. Entity-relevant ICD-codings (e.g. Lymphoma) were taken into account for the comorbidity-scoring. In addition, the specific comorbidity burden was assessed through another data-driven approach, identifying and describing the five most common comorbidities. Medical variables and measures: diagnostics (ICD-10-Code), outpatient medication (ATC-L-Code), relevant inpatient and outpatient procedures (OPS-code). Side effects (ICD-10-Code; e.g. sepsis, thrombosis, etc.). Economic variables; Inpatient stay, costs. Outcomes in terms of mortality.

Subgroup analysis A and B on patients with stem-cell-transplant

Identification via OPS-coding (auto-SCT: 5-411.0, 8-805.0; allo-SCT: 5-411.2–5-411.5, 8-805.2-8-805.5). The subgroups of patients with respective therapy were analysed for both entities in 6, 12 or 24 months after the treatment-coding. The following measures were assessed within the available follow-up period: 1.) Patient characteristics and comorbidities at the time of therapy-coding. 2.) Number and duration of hospitalisations in the 6, 12 and 24 months after therapy. 3) Costs of transplant in the 6, 12 or 24 months after SCT-coding. 4) Mortality incl. Kaplan-Meier curve in the 6, 12 or 24 months after therapy.

Prevalence and Incidence

Out of total 8.8 million individuals in the database, an annual subsample from the years 2015–2020 of ~ 3.25 million individuals were included in this analysis, being representative for the German population [21]. With, a mean of 956 prevalent patients with follicular lymphoma and 1.362 patients with diffuse large B-cell lymphoma, corresponding to a 1-year FL prevalence rate of 29,4/ 100.000 [median 30, range 25,6–31,9] and 41,9 / 100.000 [median 42,6, range 36,8–44,6] for the DLBCL-cohort, respectively. The mean incidence rate was 7,3 per 100.000 [median 7,2, range 6,7–8,1] for FL and 14,4 [median 14,3, range 13,1–15,3] for DLBCL-pts.

Patient characteristics and comorbidities

Details are shown in Table 1. The annual distribution of the TOP-5 comorbidities did not change during the observation period (Supp_Table 1).

Table 1

Patient characteristics of prevalent FL/ DLBCL cohort
	FL			DLBCL
Number of individuals per year; n absolute (n per 100.000)	n		per 100.000	n		per 100.000
2015	837	26		1205	37
2016	901	27		1324	40
2017	927	28		1349	41
2018	1012	31		1414	44
2019	1030	32		1445	44
2020	1028	32		1437	45
Age in years
Mean (SD)	67	13		69	14
Median (range)	69	18–98		71	18–99
Age group in respective year; n absolute (%)
18-39y	27	3		53	4
40-59y	210	22		262	19
60-80y	596	62		796	58
> 80y	123	13		252	18
Sex; n absolute (%)
Male	471	49		758	56
Female	485	51		605	44
Comorbidities; mean score (standard deviation)
Charlson	4,1 +/- 2,4			4,8 +/- 2,7
Elixhauser	5,2 +/- 3,0			6,1 +/- 3,3

[Description Table 1] For comorbidity scoring all variables (incl. entity-specific) were included.

Diagnostic, treatment and procedures

Diagnostic

In the inpatient-setting 33% of the FL-patients received a minimum of one CT-diagnostic, 9% an MRT and 7% an ultrasound per year. In the outpatient setting: 42% of the FL-patients received minimum one CT-diagnostic, 19% a MRT and 86% an ultrasound. Similarly, in the inpatient-setting 46% of the DLBCL-patients received a minimum of one CT-diagnostic, 18% an MRT and 9% an ultrasound. In the outpatient setting, 36% of the DLBCL-patients received a minimum of one CT-diagnostic, 16% a MRT and 74% an ultrasound.

Treatment

For outpatient FL medication on ATC-level the annual distribution was comparable between 2015 and 2017, including Rituximab, Bendamustin, Vincristin, Doxorubicin and Cyclophosphamide with descending shares. The percentage of Obinutuzumab increased between 2018 and 2020. For DLBCL patients, the distribution was comparable including Rituximab, Vincristin, Cyclophosphamid, Doxorubicin and Filgrastim/ Pegfilgrastim with descending shares. The percentage of Rituximab decreased slightly over the years. For the inpatient medication on OPS-Level, the annual distribution does not change between 2015 and 2020 (Table 2). For more detailed information, see Supp_Tables 2 & 3 in the supplements.

Table 2

Overview mean inpatient treatment procedures between 2015 and 2020 per year
	FL		DLBCL
	n	%	N	%
Total patients	956	100	1362	100
Non complex chemotherapy	85	9	265	19
Moderately complex and intensive block chemotherapy	29	3	159	12
High complex and intensive block chemotherapy	8	1	35	3
Other immunotherapy	89	9	310	23
Highly active antiretroviral therapy	0	0	7	1
Radiotherapy	15	2	50	4
CAR-T-cells	0	0	< 5	< 5
Stem cell transplant autogeneous	7	1	25	2
Stem cell transplant allogenic	< 5	< 5	7	1

Side effects:

For the prevalent FL-patients following top-5 side effects (ICD-Codings) were documented: Reaction to severe stress and anxiety (12,8%), agranulocytosis and neutropenia (7,2%), immunodeficiency with predominant antibody deficiency (5,3%), thrombosis, phlebitis and thrombophlebitis (4,9%), and acute renal failure (4,3%). For the DLBCL-pts: agranulocytosis and neutropenia (16%), Reaction to severe stress and anxiety (11,7%), acute renal failure (8,9%), Aplastic anemia due to cytostatic therapy (7,8%), other secondary thrombocytopenia not designated as transfusion refractory (7,2%).

Healthcare resource utilization (HCRU) and costs

Mean HCRU and associated costs are presented in the Tables 3 and 4.

Table 3

Physician visit and hospitalization, mean annual numbers per patient
		total pat. n	Pat. n	mean	SD	min	Median	max
FL	Number of physician consultations (n, ppt)	956	955	42	27	1	37	290
	Number of hospitalizations	956	614	2	2	0	1	15
	Inpatient stay (days)	956	614	21	45	0	3	323
DLBCL	Number of physician consultations	1362	1355	42	30	0	36	251
	Number of hospitalizations	1362	1058	3	3	0	2	34
	Inpatient stay (days)	1362	1058	29	48	0	9	335

In the FL study cohort, 64% of the patients were observed with at least one hospitalization. A rate of 78% were documented for the DLBCL patients.

Associated mean inpatient costs per patient amounted to € 6.740 per year for a FL patient and € 14.188 for the DLBCL-cohort. In the outpatient setting mean annual costs per FL patient of € 2.012 and €1.906 for DLBCL were documented. The total mean costs were €15.258 per patient (ppt) in the FL-cohort (SD 20.367) and €23.455 (SD 32.892) among patients with DLBCL. More details are shown in Table 4.

Table 4

Annual total costs for FL and DLBCL patients in €
FL	n	mean	median	min	max
2015	837	15.283	6.971	189	202.453
2016	907	15.743	7.251	101	136.487
2017	926	15.683	6.987	-	255.353
2018	1012	14.938	6.823	287	239.043
2019	1030	14.846	7.255	147	166.633
2020	1028	15.054	7.041	187	152.636
DLBCL
2015	1204	22.309	11.212	-	244.870
2016	1324	25.046	13.065	116	337.495
2017	1346	23.906	11.110	-	287.162
2018	1413	23.130	10.857	-	602.243
2019	1445	22.235	10.750	104	572.105
2020	1434	24.101	10.964	-	591.068

The distribution of costs for the mean costs per FL-patient was: 13% outpatient care, 44 inpatient care, 39% drugs and 3% remedies and aids. For the DLBCL-patients: 8% outpatient care, 60% inpatient care, 29% drugs and 3% remedies and aids.

In total, mean costs for the FL-cohort (mean n = 956pts) of €14.566.390 are documented per year, for the DLBCL patients (mean n = 1.361pts) €31.960.242, respectively.

Outcomes

Documented mortality

The annual mortality rate for the prevalent FL-patients was mean n = 47,8 patients (5%). In the DLBCL cohort n = 182 patients died (13,4%).

Subgroup analysis A: FL Patients with stem cell transplant

In the FL-cohort n = 38 patients (2,01%) received a stem cell transplant per year. An auto-SCT received 27 patients (1,27%) and 8 patients received allo-SCT (0,42%). Because of data protection (n > 5 patients) no analysis was feasible for patients with auto- and allo-SCT.

Characteristics and comorbidities

For patients with auto-SCT the mean age was 59,5y (SD: 11,68y; median: 63y; range 34-74y). The gender distribution for this cohort was n = 7 (18,4%) female and n = 20 (52,6%) male. Because of data protection, no detailed information for allo-patients can be shown. In terms of comorbidities, the mean Charlson Comorbidity Index (CCI) for autologous transplanted patients was: 4,11 (SD: 2,33; median: 3,0; range 2–5). The Elixhauser Comorbidity Score for auto-SCT patients was: 6,78 (SD: 2,65; median: 7; range 3–14).

Hospitalization during 12M after transplant

The mean number of inpatient stays for the auto-SCT cohort was 4,05 (SD: 2,52; median: 3,5; range 1–10) with a mean number of n = 67 inpatient days (SD: 69,86; median: 35; range 23–258).

Total costs transplant and 12M after

The mean total costs for patients with auto-SCT were €46.270 (SD: 21.936; median: 41.882; range 12.596–106.842). Due to 4% for outpatient care, 79% for inpatient care, 16% for medicines and 1% for remedies and aids.

Because of limited FL patients, overall survival probability cannot be shown.

Subgroup analysis C: DLBCL Patients with stem cell transplant

Over the years 2015 until 2019 n = 146 prevalent DLBCL patients (4,67%) received a stem cell transplant. A number of 117 patients received an auto-SCT (3,75%) and 23 patients an allo-SCT (0,74%). Because of data protection (n > 5 patients) no results were shown for patients with auto- and allo-SCT together.

Characteristics and comorbidities

For patients with auto-SCT the mean age at SCT-procedure was 61y (SD: 10,2y; median: 63y; range 33-77y). The sex distribution for the auto-SCT cohort was n = 42 (36%) female and n = 75 (64%) male. For the n = 23 allo-SCT patients a mean age of 52,7y (SD: 12,06y; median: 55y; range 24-67y) was documented. The sex distribution was: n = 6 pts (26%) were female and n = 17 (74%) male. In terms of comorbidities, the mean CCI-score for autologous transplanted patients were: 6,09 (SD: 2,99; median: 6,0; range 2–13). In the allo-SCT cohort a score of 4,22 (SD: 1,91; median: 4,0; range 2–9) were documented. The Elixhauser comorbidity score for auto-SCT patients was: 8,38 (SD: 2,9; median: 8; range 3–17) and 6,17 (SD: 2,46; median: 6; range 4–14) for the allo-SCT cohort.

Hospitalization in 12M after transplant

The mean number of inpatient stays in the 12M after transplant, was n = 3,9 per auto-SCT patient (SD: 2,29; median: 4; range 1–10) with a mean number of inpatient days of 79d (SD: 75,6; median: 44; range 1–318). The mean number of inpatient stays for patients with allo-SCT were 6,1 (SD: 3,38; median: 5,5; range 1–12) with a mean 183 inpatient days (SD: 116,9; median: 144; range 40–345).

Total costs during and 12M after transplant

The total costs in the 12M during and after transplant for all patients with auto-SCT (n = 95) were €5.373.020 and for the allo-SCT cohort n = 14 €2.263.269. The mean total costs were €56.558 per auto-SCT patient (SD: 45.926; median: 42.064; range 12.596–338.009). Due to 3% for outpatient care, 82% for inpatient care, 11% for medicines and 4% for remedies and aids. The mean total costs for allo-SCT patients were €161.662 ppt (SD: 75.266; median: 148.105; range 86.128–294.691) in the 12 months after coding. Due to 2% for outpatient care, 79% for inpatient care, 18% for medicines and 0% for remedies and aids.

Outcomes in terms of documented mortality after transplant

The mortality rate of the auto-SCT cohort (n = 95 pts) was 5,23% (n = 5pts) in the 12M follow-up after transplant. In the allo-SCT cohort n = < 5 patients had a documented death. For more details, see Fig. 1.

The findings of this study demonstrate the high burden of patients with malignant lymphomas (FL, DLBCL). Nearly one-thousand prevalent patients of both entities per year, the maximal documented annual inpatient stay of 335 days, given intensive therapy options like stem cell transplants, and maximal total costs of €620.000€ per patient in one year. These results indicating a challenging setting for all stakeholders in the care of these patients. Annually €87.4m for approx. n = 956 FL-patients and €191.8m for n = 1.361 DLBCL-patients were spent by third party payers between the years 2015–2020. This study generates valuable insights on FL & DLBCL-care in Germany. To our knowledge, this is likely to be one of the first comprehensive analyses of German claims data for malignant lymphomas such as FL and DLBCL.

On European level, annual prevalence of 37/100.000 for FL [ICD:C82.0, C82.1, C82.2, C82.3, C82.4, C82.5, C82.6, C82.7, C82.9] and 43/100.000 for DLBCL-patients [ICD-10 C83.3] were recently published. [22] In our German study cohort, the FL prevalence extrapolated for Germany was slightly lower (30,3/100.000). The extrapolated prevalence for the DLBCL cohort was 42,4/100.000 what is comparable to aforementioned European data. One reason for these lower FL-rates can be the methodologic difference by the including ICD-codes. Also, there is a trend of rising prevalence over the observation period. Between 2015 and 2020 the prevalence increased by 23% for FL and 22% for DLBCL. This trend of increasing patient numbers is comparable with German data, provided by the “Krebs in Deutschland für 2017/2018”-report published by the governmental Robert-Koch institute [4].

In terms of the age-distribution, the majority of the patients had a documented age above 60 years. Up to 75% (FL) and 76% (DLBCL) of the respective patients were in this age group. This observation must be interpreted in a broader view. The number of incident NHL-patients with an age of more than 80years are highest. Discussed in context of a higher mortality-risk for patients > 75y, the low numbers in the eldest age-groups in our prevalent cohort are plausible. [4] In terms of gender distribution, the InGef-cohort is almost in line with Dürig J et al. gender is balanced in the FL group (men: 49% men), in the DLBCL group a the proportion of men (57.7%)was slightly higher [23]. This observation is also in line with previous publications. [5, 16, 17].

No German publication on comorbidities has been found, therefore no national comparisons are possible. Yang X. et al showed in a US claims data analysis on n = 2.500 DLBCL patients a mean CCI-Index number for prevalent patients of 2.3 (SD ± 2.4) [24]. In our study cohort CCI-score for the prevalent DLBCL cohort was 4,8 (SD ± 2.7). The CCI-score is clearly higher, because of e.g. different methodological approaches (entity not excluded). For FL-patients no public available information has been found. Beside the scores, the individual underlying variables indicate a huge patient burden (Supplement Table 1). For example, about 30% of all prevalent patients in both entities had a depression in our study cohort. In a previous publication for Germany a depression-rate for NHL-pts of 22,3% within 10-years after index date was communicated [25]. Also the documented side effects indicate the high burden for these patients. Here, a clear difference between the two entities was documented. The shares of agranulocytosis and neutropenia, reaction to severe stress and anxiety, and acute renal failure are more than doubled for DLBCL patients. This observation as well as the more intense treatment regimens might be responsible for the documented longer inpatient-days in the DLBCL-cohort. In addition, the mean numbers of diagnostic procedures shown underscore the high resource use, as all patients underwent at least one procedure. However, we assume that this number is underestimated and that patients have significantly more procedures.

Other results on treatment-details, are generally consistent with the expectations of clinical experts and previous international research. Thus, a substantial percentage of chemotherapy-based treatment approaches for the DLBCL cohort (e.g. R-CHOP) is documented. [26] In contrast, in the FL-cohort 25% of the prevalent patients received Rituximab in the ambulant setting only. In addition, the increasing usage of innovative treatment after market-approval were documented. After its approval in September 2017, the Obinutuzumab-use for FL-patients continuously increased between 2018 and 2020 [27].

When discussing patient-burden, hospitalization-rates are an additional indicator of previously discussed aspects. The results identified a mean of 20,7 inpatient days in the FL cohort and 29,3 days for the DLBCL patients. The number of hospitalizations were n = 2,0 and n = 2,9 admissions, in respective. The maximum number of n = 323 (FL) and n = 336 (DLBCL) inpatient days indicate major expenditures of resources, and a huge burden of disease for individual patients. This observation of huge efforts for a small number of high risk patients, is consistent with a German DLBCL study [28]. In this retrospective analysis of relapsed and refractory DLBCL-patients, a mean number of 63 inpatient days (median 66; range 17–123; SD ± 36) and 5 admissions (3; 1–12; ±3) were documented in DLBCL patients with > 3 lines of therapy.

However, in our study the annual costs for inpatient care contributed to highest shares of total cost for both entities and over the total observation period. A high proportion of inpatient cost was also noted in several international real-world cost analysis on DLBCL and FL. [29–31] A recent German claims data analysis on DLBCL-patients documented hospitalization as the main cost driver with 71%. The time-unadjusted absolute costs sum up to €59,868 (43,331), €35,870 (37,387), and €28,832 (40,540) during first-line, second-line, and third-line treatments, respectively. [32] Due to methodological differences (e.g. results classified in lines of therapy only) no detailed comparison were performed. International publications also show comparable results: In a Canadian study of DLBCL patients, the inpatient stay for second-line treatment was the largest cost driver (62%)[30]. Tsutsué et al. showed in a Japanese claims data analysis, that the majority of the overall costs as well as per-treatment line were due to inpatient costs (n = 6,821) of 47,903.08 USD (SD, 47,497.30; range, 247.43–488,296.86) [29]. A major factor in this context is the choice of therapy. One example of a treatment approach that has a huge economic impact is the stem cell transplantation. In a Canadian study, autologous SCT and hospitalization contributed the most to direct costs for DLBCL patients in more than three lines of therapy [33]. We discussed this in context of the subgroup analysis on SCTs, in the following text.

In general, the mean and median numbers of all cost-data differ significantly because of the wide range of min and max numbers, with a maximal annual cost of €255.353 per patient in FL and €602.243 for the DLBCL. A small number of patients with very high total costs were documented. From 2018 to 2019/20 the maximal costs almost doubled in the DLBCL-cohort. This significant increase may be caused by a higher number of treatment-approaches with cost-intensive innovative / personalized medicines. In total, mean costs of €15.4m are documented per year in the FL-cohort, in comparison to €34.6m in the DLBCL patients. The mean annual costs in years 2017 to 2020 amounted to 0.3% (FL) and 0,7% (DLBCL) of the German statutory health insurance expenses in these years on antineoplastic agents (approximately €5 billion) [34].

In terms of outcomes, we focussed on mortality and survival. The mean annual mortality rate for the prevalent FL-patients was 5% and 13,4% for the DLBCL-cohort. Since these cohorts are a cross-section of all patients in the corresponding year, the outcome-results of the SCT subgroup were discussed only. Regarding the outcomes in the subgroup analysis on stem cell transplanted patients (Fig. 1), a recent Canadian study on FL-patients demonstrated also an potential long-term benefit of SCT in Canada [35]. Because of the insufficient evidence level on German data for both entities, no further comparison with national data was possible. However, when discussing on treatment and respective outcome, innovative approaches must be set into perspective e.g. CAR-T cell therapies [36].

As an addition, in the subgroup analysis, the mean 12M-total cost after autologous SCT were €46.270 for FL and €56.558 for the DLBCL patients. The mean 12M–costs for DLBCL-patients with allo-SCT were €161.662. Mayerhoff et al. reported direct costs of €230,399/patient (DLBCL/FL allogeneic) and €107,457/patient (DLBCL/FL autologous) for Germany. These reported costs are substantially higher, because they were summed up in the period of two quarters before and eight quarters after SCT. [37] Moertl et al. documented mean treatment costs per DLBCL-patient with auto-SCT of €55,468 and €131,264 for allo-SCT in the clinical setting[28]. Further research and detailed information are needed to put conventional treatments in the context of innovative treatment approaches, such as CAR T-cell therapy, which ranged between 276 086 EUR and 328 727 EUR [38].

Summarizing, in terms of rising prevalence of haematological malignancies in Germany, comprehensive care for patients can lead to high costs for health systems and places pressure on public budgets. Our results can be used as a baseline for future economic studies, in the context of innovative lymphoma therapies in Germany.

Certain factors limit our findings. The analyses were based on health claims records, which are collected for billing purposes and not primary for research reasons. Therefore, all results depend on quality of coding. Because of the high level of data protection in Germany, individual case validation was not possible and no results for a patient count of n < 5 could be displayed. Because of general limitations in health claims datasets, classification of socioeconomic status, clinical details (e.g. tumor status, lines of therapy) or quality of life (QoL) criteria is impossible. Despite this lack of data, the impact of high-dose chemotherapies on the quality of life of e.g. FL patients should not be neglected [39]. Another limitation of the health claims data is the missing of comprehensive information on specific treatments. For instance, singular medicines dispensed in the inpatient setting cannot be assessed separately as these costs are usually included in the compensation schemes for diagnosis related groups (DRG). On the other hand, this also reflects a major strength of this study as it evaluates overall costs and resource utilization based on the perspective of health insurances with a high rate of data completeness. Similarly, the large and representative sample size is a huge strength.

In summary, in the underlying German health insurance claims database, the number of FL and DLBCL continuously increased between 2015 and 2020. The number and length of inpatient stays indicates a high burden for the patients and their families. Especially for patients with relapsed or refractory (r/r) course of disease, it can be associated with an uncertain prognosis. In addition, the costs for r/r patients who require intensive treatments such as SCTs are significant. For a more holistic view future effort should include linkage to additional data sources, e.g. prospective registries, regional cancer registry to enable comprehensive information on patient journeys, treatment patterns and outcome analysis. However, our results from health insurance claims data provide complementary information for initial discussions with payers, administrators and politician in the context of access to innovative treatments.

Conflict of interest:

Karin Berger is employed at the LMU Klinikum, Department Haematology / Oncology. D. Beier and D. Pawlowska-Phelan are employed by InGef-Institute for Applied Health Research Berlin GmbH, which received funding from LMU Klinikum. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Ethical considerations

This study was approved by a Scientific Committee, consisting of clinical experts from LMU Klinikum and InGef-Insitute for Applied Health Research Berlin. Due to the non-interventional nature of this research, which used a retrospective anonymized claims dataset, no ethical approval was required for this study. The study followed all the dictates of the Declaration of Helsinki.

Competing Interests

Karin Berger is employed at the LMU-Clinic, Department Haematology / Oncology. D. Beier and D. Pawlowska-Phelan are employed by InGef-Institute for Applied Health Research Berlin GmbH, which received funding from LMU. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Funding Statement:

The conduct of this study has been supported by a research grant from Novartis Pharma GmbH; InGef received research funding by LMU Klinikum. Novartis Pharma GmbH provided financial support, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript

Author Contribution

KB and BM contributed half/half to the development of the conceptional study design, critical interpretation of results, and writing the draft as well as the final version of the article. MD and MvB, supported as clinical experts on lymphoma and have been involved in critical interpretation of results. DB and DPP conducted the data collection and data analysis in consultation with KB and BM. All authors were involved in critically reviewing the article and gave approval of the version to be published. The manuscript was prepared according to the ICMJE Recommendations.

Acknowledgement

Funding Statement:The conduct of this study has been supported by a research grant from Novartis Pharma GmbH; InGef received research funding by LMU Klinikum. Novartis Pharma GmbH provided financial support, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript

Data Availability

The data used in this study cannot be made available in the article, the supplemental files, or in a public repository due to German data protection laws (Bundesdatenschutzgesetz). To facilitate the replication of results, anonymized data used for this study are stored on a secure drive at the InGef - Institute for Applied Health Research Berlin. Access to the raw data used in this study can only be provided to external parties under the conditions of a cooperation contract and can be accessed upon request, after written approval ([email protected]), if required.

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Competing interest reported. Karin Berger is employed at the LMU-Clinic, Department Haematology / Oncology. D. Beier and D. Pawlowska-Phelan are employed by InGef-Institute for Applied Health Research Berlin GmbH, which received funding from LMU. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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You are reading this latest preprint version

Follicular lymphoma or diffuse large B-cell lymphoma: a population based analysis of epidemiological and health economic aspects in Germany

Status:

Version 1

Abstract

Figures

INTRODUCTION

MATERIALS AND METHODS

STUDY DESIGN

DATA SOURCE

Case definition

Study variables

Subgroup analysis A and B on patients with stem-cell-transplant

RESULTS

Prevalence and Incidence

Patient characteristics and comorbidities

Diagnostic, treatment and procedures

Diagnostic

Treatment

Side effects:

Healthcare resource utilization (HCRU) and costs

Outcomes

Documented mortality

Subgroup analysis A: FL Patients with stem cell transplant

Characteristics and comorbidities

Hospitalization during 12M after transplant

Total costs transplant and 12M after

Subgroup analysis C: DLBCL Patients with stem cell transplant

Characteristics and comorbidities

Hospitalization in 12M after transplant

Total costs during and 12M after transplant

Outcomes in terms of documented mortality after transplant

DISCUSSION

CONCLUSION

Declarations

Conflict of interest:

Ethical considerations

Competing Interests

Funding Statement:

Author Contribution

Acknowledgement

Data Availability

References

Additional Declarations

Supplementary Files

Status:

Version 1