Abstract
Aim: To describe patient and treatment characteristics associated with bevacizumab BS-Pfizer, rituximab BS-Pfizer and trastuzumab BS-Pfizer and their reference products in Japan.
Methods: This retrospective observational study used an administrative claims database to identify patients with ≥1 biosimilar or reference product prescription from 2019 to 2022 for approved indications. Descriptive statistics were calculated.
Results: Overall, 14–39% of biosimilar-prescribed patients initiated therapy with reference products. Biosimilar utilization significantly increased from 2019 to 2022. The most-commonly prescribed concomitant class of therapy with biosimilars was antineoplastic therapy.
Conclusion: Reference products were most frequently prescribed among the Japanese cohorts, but substantial and increasing proportions received biosimilars over time. Future studies should extend our initial insights to assess biosimilar clinical outcomes in Japanese settings.
Keywords: : B-cell non-Hodgkin's lymphoma, bevacizumab, biosimilars, breast cancer, colorectal cancer, gastric cancer, Japan, non-small-cell lung cancer, real-world utilizationrituximab, trastuzumab
Plain Language Summary
This study examines the adoption of cancer biosimilar therapies in Japan from 2019 to 2022. Cancer biosimilars are complex treatments that closely resemble established cancer therapies already available in Japan. We looked into the characteristics of patients receiving three specific biosimilars – bevacizumab BS-Pfizer, rituximab BS-Pfizer and trastuzumab BS-Pfizer. We also investigated where patients received biosimilar treatment, other therapies they received alongside biosimilars and the proportion of patients using these therapies each year during the study. Our analysis utilized data from the ‘Medical Data Vision’ database, which records care provided in hospitals across Japan. We analyzed patient demographics and treatment patterns, and compared different groups using statistics to identify significant differences. Notably, we observed that between 14 and 39% of patients initially started treatment with the original version of the drug on the market, known as the ‘reference product,’ before switching to the biosimilar. Furthermore, our findings revealed a significant increase in the use of biosimilars each year during the study period. Biosimilars were most-commonly used alongside chemotherapy drugs. These initial findings shed light on the patient population using cancer biosimilars in Japan and the treatment contexts in which they are utilized. Future research should delve deeper into aspects such as cost of care, patient survival, side effects and other pertinent factors related to the use of biosimilars in cancer care in Japan.
Plain language summary
Article highlights.
The use of oncology biosimilars in clinical practice in Japan is limited, at least partly, by the lack of evidence demonstrating real-world outcomes in Japanese patients.
This retrospective observational study provides descriptive insights into the real-world use of bevacizumab, rituximab and trastuzumab biosimilars in Japan for colorectal cancer and non-small-cell lung cancer, B-cell non-Hodgkin's lymphoma and HER2-positive breast and gastric cancers, respectively.
We observed significant increases in biosimilar utilization over time from 2019 to 2022.
Across indications, from 14 to 39% of biosimilar-prescribed patients switched to the biosimilar after initiating therapy with the corresponding refence product.
The most commonly prescribed concomitant class of therapy with biosimilars was antineoplastic therapy across each setting.
This study has several limitations that should be noted, including that the Medical Data Vision hospital-based claims database has missing data for some variables, lacks detailed diagnosis and prognosis data (histology, Eastern Cooperative Oncology Group performance status, disease severity, etc.) and does not record deaths that occur outside the hospital.
Initial real-world insights in Japan demonstrate comparable patient characteristics, treatment patterns and treatment duration between bevacizumab, rituximab and trastuzumab biosimilar and originator-treated patients.
1. Background
A biosimilar (BS) is a biological product that meets high standards for comparability to an existing, approved biological product (also known as the reference product) in terms of structure, quality, safety and efficacy [1,2]. These entities are developed and approved based on scientific evidence demonstrating their equivalence to the reference product. Since the availability of the first Somatropin BS in 2009 in Japan [3], the Japan Pharmaceuticals and Medical Devices Agency (PMDA) has approved 32 BS products based on 16 active pharmaceutical ingredients as of 2022 [4]. In contrast, the European Medicine Agency (EMA) has approved 93 BS [5], the US FDA has approved 41 BS [6] and Health Canada has approved 52 BS [7].
Biosimilar development has been particularly prevalent in oncology care. To date, the PMDA has approved BS for the foundational oncology monoclonal antibodies bevacizumab, rituximab and trastuzumab. The similarity between Zirabev™ (bevacizumab BS-Pfizer, bevacizumab BS1) and the reference product Avastin® (Genentech Inc., CA, USA, and Roche Registration LTD, Welwyn Garden City, UK) was first confirmed in 2019 in a randomized study on patients with non-squamous non-small-cell lung cancer (NSCLC) treated in combination with carboplatin and paclitaxel [8]. Bevacizumab BS1 was approved in Japan for unresectable advanced/recurrent colorectal cancer (CRC) the same year based on extrapolation and then extended to unresectable advanced/recurrent NSCLC except squamous cell carcinoma [3,9]. RUXIENCE™ (rituximab BS-Pfizer, rituximab BS2 to Rituxan® [rituximab]) was approved in Japan for treatment of CD20-positive B-cell non-Hodgkin's lymphoma (NHL), immunosuppressed CD20-positive B-cell lymphoproliferative disease, granulomatosis polyangiitis and microscopic polyangiitis in 2019 [3]. The REFLECTIONS B328-06 clinical comparative study (ClinicalTrials.gov, NCT02213263) had previously evaluated the efficacy, safety and immunogenicity, pharmacokinetics and pharmacodynamics of rituximab BS2 and found no clinically meaningful differences as compared with the reference product in patients with CD20-poistive low tumor burden follicular lymphoma up to week 52 [10]. The similarity between Trazimera™ (trastuzumab BS-Pfizer, trastuzumab BS3) and the reference product Herceptin® (Genentech) was first demonstrated in nearly 500 patients across 20 countries, including Japan [11–15]. In Japan, trastuzumab BS3 has been available since 2019 based on results of clinical studies conducted on HER2-positive breast cancer patients, but an approval was also granted for the indication of HER2-positive unresectable advanced/recurrent gastric cancer based on extrapolation [16,17]. Data extrapolation is a well-established principle rooted in the application of findings from a study conducted on one indication to draw inferences for another indication. Its purpose is to prevent unnecessary clinical trials and facilitate the optimal allocation of resources for clinical research [18,19].
Years of targeted interventions by the Japanese government have significantly expanded the market for generic medicines, with health policy measures supporting generic substitution playing a crucial role. With the aging population and the emergence of generic manufacturers in emerging markets, the national generic sector is likely to continue expanding [20]. Likewise, BS can serve an important role in the Japanese healthcare sector as they serve as lower cost alternatives to reference products, and can potentially deliver cost savings to the healthcare markets that can be reinvested in treating more patients with biologic therapies or allocated to benefit patients and healthcare systems in other ways [8,21]. As per the Japanese national health insurance drug pricing system, the first National Health Insurance (NHI) price for BS is typically 30% less than corresponding reference products [22]. Thus, expansion of BS usage has been anticipated to reduce national healthcare costs, consistent with supportive measures for their development by the Japanese government.
Despite the variety of oncology BS available for patients in Japan and the cost-saving potential of BS use, challenges to BS adoption include a lack of directed education to providers, formulary exclusion and scarce long-term safety data [23–25]. Japanese surveys on the recognition and understanding of BS have revealed a lack of familiarity with BS among physicians, pharmacists and patients, and several medical professionals have voiced their concerns with insufficient clinical data [26,27]. Physicians sought more comprehensive information on the quality, efficacy and patients' cost between reference product biologics and their BS to support evidence-based communication with patients [28]. For this reason, development and dissemination of real-world evidence is critical to increase awareness among patients and physicians regarding the benefits and challenges of BS as well as their extrapolation to other indications.
The objective of this retrospective, observational study is to provide initial descriptive insights to address key evidence gaps about bevacizumab, rituximab and trastuzumab BS use in Japan with real-world evidence about patient characteristics, treating hospital characteristics and treatment patterns in oncology care. This type of exploratory approach can be particularly useful to provide insights about the real-world treatment landscape in therapeutic areas with limited research conducted to date – as is the case with oncology biosimilar use in Japan.
2. Methods
2.1. Study data source
This study used Medical Data Vision (MDV), a large Japanese nationwide hospital-based database containing anonymized data from inpatient and outpatient settings, including standardized healthcare insurance claims data provided by hospitals using the Japanese Diagnosis and Procedure Combination (DPC) [29]. DPC is a fixed payment reimbursement system for acute inpatient care introduced in 2003 [30,31]. The study period was 1 January 2019 to 30 June 2022. As of March 2023, the MDV database included approximately 42.32 million patients from more than 460 DPC hospitals in Japan [32], and has been used to study oncology care in Japan in a variety of recently published studies [33–37]. MDV contains de-identified information such as patient sex, birth year, departments visited, date of medical service, diagnostic codes (International Statistical Classification of Diseases and Related Health Problems 10th Revision [ICD10] codes and local codes), hospitalizations, medical procedures and test orders, surgeries and prescriptions [32].
2.2. Study design
Diagnoses were identified based on ICD-10 codes. Accordingly, the following ICD-10 codes were applied: C18.x, C19.x, C20.x for CRC and C34.x for NSCLC; C82.x, C83.x, C85.x, C88.4 for NHL; C50.x for breast cancer (BC) and C16.x for gastric cancer (GC). The variable of cancer stage in the MDV database was used to identify BC, CRC and NSCLC patients with metastatic disease. For patients missing this information, algorithms based on clinical findings were used to identify early and metastatic BC patients and metastatic CRC and NSCLC patients. In brief, patients with NSCLC and BC were considered to have metastatic disease if they had undergone systemic antineoplastic therapy without a curative surgery, systemic antineoplastic therapy 180 days after a curative surgery, or have had a secondary malignancy after the diagnosis of interest. Patients with BC and not identified with metastasis were considered to have early-stage breast cancer (Supplementary Figures S1–S3).
The treatment initiation date was considered the index date. The washout period was defined as the 24 months before initiation of the treatment of interest, and this period was used to capture treatments or medication use and corresponding oncology diagnoses. The patients were followed from the treatment initiation date until censoring due to lost to follow-up (i.e., with no further information of dispensation or any other medical acts), death or the end of the study period on 30 June 2022.
2.3. Study population
The study population was comprised of adult patients (≥18 years) with at least one claim for BS1, BS2 or BS3 or the corresponding reference products between 1 January 2019 and 30 June 2022, and had at least one diagnosis code for the approved indication (CRC and NSCLC for BS1, NHL for BS2, and BC and GC for BS3) for up to 2 years prior to BS or reference treatment initiation (i.e., the index date).
For each cancer, three subgroups of patients (medication cohort) were defined as follows: patients who had only the reference product and did not have any BS products during the study period; those who had only Pfizer BS and did not have the reference product or any other BS products during the study period; and those who received the reference product at least once before Pfizer BS (indicating a switch from the reference product to Pfizer BS).
2.4. Statistical analyses
We documented the following variables for patients included in the study population: age, gender, BMI, smoking status at the treatment initiation date and Charlson Comorbidity Index (CCI) during 6 months before the initiation date. Information about hospital characteristics, such as hospital scale (number of beds) and department of care, was also collected. Treatment patterns were assessed for the three BS products and included treatment follow-up duration (number of days of continuous therapy with a product before discontinuation) and treatment switch (at least one claim of a reference product, followed by at least one claim of the corresponding Pfizer BS). Information regarding concomitant treatments, which are treatments received during the period from the initiation date of the BS product (index date) to the last dispensation of the BS product, were also collected.
Continuous variables were summarized as means with standard deviations (SDs) and medians with interquartile ranges (IQR). Categorical variables were expressed as frequencies and percentages. Bivariate analyses of patient characteristics were conducted using Wilcoxon test for continuous variables and a chi-square test (or Fisher exact test when it was applicable) for categorical variables. Patient and hospital characteristics were compared between the BS and reference product groups and those who switched from the reference product to BS (the switcher population) for each disease. Across analyses, statistical significance was assessed as p < 0.05.
Kaplan-Meier time-to-event analysis was applied to evaluate the treatment follow-up duration for patients receiving each product of interest, BS (including switched patients) or reference product, starting from the initiation date (index date). The treatment initiation date for patients who switched treatment from reference product to biosimilar was the biosimilar start date. Treatment discontinuation was defined as a period of ≥60 days without the given treatment or death. Censoring was applied when no claims information was available after the last dispensation (indicating lost to follow-up), or if the study's end date was less than 60 days from the last dispensation. The prescription trends for BS and their reference products within the study period were evaluated using the Cochrane-Armitage trend analyses. These analyses were for descriptive purposes and were not adjusted for potential confounders.
Statistical analyses were conducted using the statistical software SAS® version 9.4 (SAS Institute Inc, NC, USA). This observational study was performed in accordance with ethical principles consistent with the Ethical Guidelines for Biomedical Research Involving Human Subjects, the Declaration of Helsinki and the Japanese Act on the Protection of Personal Information. According to the Japanese Ethical Guidelines for Medical and Health Research Involving Human Subjects, institutional review board approval and patient informed consent were not required for this observational study as it used secondary data without any identifiable patient information.
3. Results
3.1. Bevacizumab in colorectal cancer & non-small-cell lung cancer
3.1.1. Patient characteristics
We identified 19,811 patients with an ICD-10 code indicating CRC diagnosis and 3,645 patients with an ICD-10 code corresponding to NSCLC diagnosis who had at least one record of bevacizumab treatment (Table 1). Among CRC patients, 2532 were prescribed BS1 and 17,279 were prescribed the reference product. In total, 2059 (81.3%) BS1-prescribed and 14,656 (84.8%) reference product-prescribed CRC patients were identified with metastatic cancer (Supplementary Figure S1).
Table 1.
Demographics and clinical characteristics of colorectal and non-small-cell lung cancer patients treated with bevacizumab.
| Colorectal Cancer (N = 19811) | Non-Small-Cell Lung Cancer (N = 3645) | |||||||
|---|---|---|---|---|---|---|---|---|
| Biosimilar | Reference | Biosimilar Switch | Biosimilar No Switch | Biosimilar | Reference | Biosimilar Switch | Biosimilar No Switch | |
| N = 2532 | N = 17279 | N = 974 (38.5%) | N = 1558 (61.5%) | N = 411 | N = 3234 | N = 121 (29.4%) | N = 290 (70.6%) | |
| Mean (±SD) | 67.3 (±10.9) | 68 (±10.7) | 67.8 (±10.4) | 67 (±11.2) | 65.9 (±10.4) | 66.8 (±9.6) | 65.7 (±10.1) | 66 (±10.6) |
| Median | 69 | 70 | 69 | 69 | 68 | 69 | 67 | 68 |
| [Q1; Q3] | [61; 75] | [62; 75] | [62; 75] | [61; 75] | [60; 73] | [61; 73] | [59; 73] | [60; 73] |
| Age categories | ||||||||
| <40 | 39 (1.5%)‡ | 267 (1.5%) | 8 (0.8%) | 31 (2.0%) | 7 (1.7%) | 25 (0.8%) | 3 (2.5%) | 4 (1.4%) |
| 40–64 | 799 (31.6%) | 5055 (29.3%) | 303 (31.1%) | 496 (31.8%) | 152 (37.0%) | 1075 (33.2%) | 45 (37.2%) | 107 (36.9%) |
| 65–74 | 1040 (41.1%) | 7102 (41.1%) | 404 (41.5%) | 636 (40.8%) | 179 (43.6%) | 1494 (46.2%) | 53 (43.8%) | 126 (43.4%) |
| 75–84 | 600 (23.7%) | 4402 (25.5%) | 236 (24.2%) | 364 (23.4%) | 69 (16.8%) | 604 (18.7%) | 20 (16.5%) | 49 (16.9%) |
| 85 ≤ | 54 (2.1%) | 453 (2.6%) | 23 (2.4%) | 31 (2.0%) | 4 (1.0%) | 36 (1.1%) | 20 (16.5%) | 4 (1.4%) |
| Gender | ||||||||
| Male | 1447 (57.1%) | 10105 (58.5%) | 523 (53.7%)† | 924 (59.3%) | 244 (59.4%) | 1881 (58.2%) | 72 (59.5%) | 172 (59.3%) |
| Female | 1085 (42.9%) | 7174 (41.5%) | 451 (46.3%) | 634 (40.7%) | 167 (40.6%) | 1353 (41.8%) | 49 (40.5%) | 118 (40.7%) |
| BMI | ||||||||
| Mean (±SD) | 23.3 (±3.9) | 23.4(±4.5) | 23.4 (±4.0) | 23.2 (±3.9) | 23.0 (±3.5) | 23.3 (±3.7) | 23.5 (±3.7) | 22.8 (±3.4) |
| Median | 22.9 | 23.0 | 23.1 | 22.9 | 22.7 | 23.1 | 23.0 | 22.7 |
| [Q1; Q3] | [20.6; 25.4] | [20.7; 25.5] | [20.7; 25.5] | [20.5; 25.4] | [20.9; 24.9] | [20.8; 25.3] | [21.3; 25.3] | [20.7; 24.8] |
| Charlson Comorbidity Index categories | ||||||||
| [0; 2] | 266 (10.5%)† | 2086 (12.1%) | 91 (9.3%) | 175 (11.2%) | 26 (6.3%) | 192 (5.9%) | 10 (8.3%)† | 16 (5.5%) |
| [3; 5] | 330 (13%) | 2179 (12.6%) | 120 (12.3%) | 210 (13.5%) | 79 (19.2%) | 598 (18.5%) | 22 (18.2%) | 57 (19.7%) |
| 6 ≤ | 1936 (76.5%) | 13014 (75.3%) | 763 (78.3%) | 1173 (75.3%) | 306 (74.5%) | 2444 (75.6%) | 89 (73.6%) | 217 (74.8%) |
| Smoking status | ||||||||
| Yes | 1226 (48.4%) | 8105 (46.9%) | 471 (48.4%) | 755 (48.5%) | 248 (60.3%) | 1852 (57.3%) | 80 (66.1%) | 168 (57.9%) |
| No | 1042 (41.2%) | 8122 (47%) | 438 (45%) | 604 (38.8%) | 149 (36.3%) | 1236 (38.2%) | 37 (30.6%) | 112 (38.6%) |
| Missing | 264 (10.4%) | 1052 (6.1%) | 65 (6.7%) | 199 (12.8%) | 14 (3.4%) | 146 (4.5%) | 4 (3.3%) | 10 (3.4%) |
p-value < 0.05 for Wilcoxon, or Chi2 (or Fisher exact) tests when applicable.
p-value < 0.05 for Cochrane-Armitage trend test.
The patient characteristics were similar between the BS1-prescribed, reference product-prescribed and metastatic groups. The mean (SD) ages of patients from the BS1 and reference product groups were 67.3 (10.9) and 68.0 (10.7) years, and 66.9 and 69.2% were at least 65 years old at bevacizumab treatment initiation, respectively. The percentage male (57.1 and 58.5%) and mean (SD) BMI (23.3 [3.9] vs 23.4 [4.5] kg/m2) were similar between the BS1 and reference product groups, respectively. About half of the patients from both groups were smokers (48.4% from BS1 and 46.9% from reference product), and the majority had a CCI score >3 (89.5% from BS1 and 87.9% from reference product).
Among NSCLC patients, 411 (11.2%) received BS1 and 3,234 (88.8%) received reference product treatment (Table 1). Overall, 321 (78.1%) BS1-prescribed and 2673 (82.7%) reference product-prescribed patients were identified with metastatic disease (Supplementary Figure S2). For BS1 and reference product groups, mean (SD) age at bevacizumab initiation was 65.9 (10.4) and 66.8 (9.6) years, and proportion ≥65 years old at bevacizumab treatment initiation was 61.4 and 66.0%, respectively. The percentage of men (59.4 and 58.2%) and mean (SD) BMI (23.0 [3.5] vs 23.3 [3.7] kg/m2) were similar between the BS1 and reference product groups. For BS1 and reference product groups, 60.3 and 57.3% patients were smokers, and 93.7 and 94.1% had a mean CCI score >3 in the 6 months prior to treatment initiation.
3.1.2. Hospital characteristics
The hospital characteristics of bevacizumab-prescribed patients with CRC and NSCLC are described in Supplementary Table S1. Among those who received BS1 treatment for CRC, 1,194 and 1,337 visits were registered in the medicine and surgery department, respectively. Among those who received BS1 treatment for NSCLC, 351 and 77 visits were recorded in the medicine and surgery department, respectively. Among CRC patients who received the reference product, 6784 visits to the medicine department and 11,794 to the surgery department were reported. Among NSCLC patients who received the reference product, 2926 and 610 visits to the medicine and surgery department, respectively, were recorded. Only 1069 (5.4%) CRC patients (132 BS1-prescribed and 937 reference product-prescribed) and 106 (2.9%) NSCLC patients (5 BS1-prescribed and 101 reference product-prescribed) were treated in hospitals with <200 beds.
3.1.3. Treatment utilization patterns
Among BS1-treated patients with CRC and NSCLC, 974 (38.5%) and 121 (29.4%) switched to BS1 after initiating treatment with the reference product (Table 1). The median (Q1, Q3) treatment follow-up duration was 217 (87, 427) and 168 (63, 350) days for BS1-prescribed and reference product-prescribed CRC patients and 219 (90, 469) and 141 (55, 287) days for BS1-prescribed and reference product-prescribed NSCLC patients, respectively (Figure 1). The median (Q1, Q3) treatment follow-up duration for BS-treated patients who switched from the reference product and for those without switching was 252 (105, 459) and 196 (77, 425) days for CRC and 283 (144, 812) and 181 (70, 324) days for NSCLC, respectively (Supplementary Figure S3).
Figure 1.
Unadjusted Kaplan-Meier curves of treatment follow-up duration in patients treated with bevacizumab. (A & B) In colorectal, and (C & D) in non-small-cell lung cancer. Lines 1 & 2 on the x-axis show the number of patients at risk in each group. Line 1 shows bevacizumab biosimilar (BS) patients, and Line 2 shows patients treated with bevacizumab reference (Ref) product. Follow-up discontinuation is defined as ≥60 days without a treatment record.
BS1 utilization increased from 2019 to June 2022 among the analyzed populations in both CRC and NSCLC (both p < 0.001; Supplementary Figure S4A & B ) and positively correlated to the hospital size for NSCLC (p < 0.05; Supplementary Table S1). Across the same period, the proportion of reference product prescriptions decreased from 100% in 2019 to about 70% in June 2022 among the analyzed CRC and NSCLC patients.
3.1.4. Concomitant treatment patterns among BS1-prescribed patients
The most common combination with BS1 was antimetabolite antineoplastic + folate analog + platinum-containing antineoplastic (n = 561, 22.1%) for CRC and monoclonal antibody + platinum-containing antineoplastic + taxane (n = 90,21.9%) for NSCLC. The concomitant treatment patterns identified for BS1-prescribed CRC and NSCLC patients are described in Supplementary Tables S2 & S3, respectively.
3.2. Rituximab in B-cell non-Hodgkin lymphoma
3.2.1. Patient characteristics
We identified 8387 patients with an ICD-10 code corresponding to NHL diagnosis who had at least one record of rituximab treatment, including 1149 (13.7%) patients prescribed BS2 and 7238 (86.3%) prescribed the reference product (Table 2).
Table 2.
Demographics and clinical characteristics of non-Hodgkin lymphoma patients treated with rituximab.
| Biosimilar | Reference | Biosimilar Switch | Biosimilar No Switch | |
|---|---|---|---|---|
| N = 1149 | N = 7238 | N = 215 (18.7%) | N = 934 (81.3%) | |
| Age | ||||
| Mean (±SD) | 70.9 (±12.4) | 70.6 (±11.7) | 69.7 (±12.1) | 71.1 (±12.4) |
| Median | 72 | 72 | 71 | 73 |
| [Q1; Q3] | [65; 80] | [65; 79] | [62; 78] | [65; 80] |
| Age categories | ||||
| <40 | 25 (2.2%) | 136 (1.9%) | 6 (2.8%)‡ | 19 (2.0%) |
| 40–64 | 261 (22.7%) | 1651 (22.8%) | 57 (26.5%) | 204 (21.8%) |
| 65–74 | 377 (32.8%) | 2466 (34.1%) | 74 (34.4%) | 303 (32.4%) |
| 75–84 | 369 (32.1%) | 2366 (32.7%) | 60 (27.9%) | 309 (33.1%) |
| 85 ≤ | 117 (10.2%) | 619 (8.6%) | 18 (8.4%) | 99 (10.6%) |
| Gender | ||||
| Male | 599 (52.1%) | 3865 (53.4%) | 121 (56.3%) | 478 (51.2%) |
| Female | 550 (47.9%) | 3373 (46.6%) | 94 (43.7%) | 456 (48.8%) |
| Charlson Comorbidity Index categories | ||||
| [0; 2] | 266 (23.2%)†,‡ | 1975 (27.3%) | 30 (14.0%)†,‡ | 236 (25.3%) |
| [3; 5] | 618 (53.8%) | 3811 (52.7%) | 122 (56.7%) | 496 (53.1%) |
| 6 ≤ | 265 (23.1%) | 1452 (20.1%) | 63 (29.3%) | 202 (21.6%) |
| BMI | ||||
| Mean (±SD) | 23.3 (±4.0) | 23.3 (±3.8) | 23.4 (±4.2) | 23.3 (±4.0) |
| Median | 22.9 | 23.0 | 23.1 | 22.9 |
| [Q1; Q3] | [20.6; 25.5] | [20.7; 25.3] | [20.5; 25.2] | [20.6; 25.5] |
| Smoking status | ||||
| Yes | 365 (31.8%) | 2484 (34.3%) | 77 (35.8%) | 288 (30.8%) |
| No | 695 (60.5%) | 4260 (58.9%) | 128 (59.5%) | 567 (60.7%) |
| Missing | 89 (7.7%) | 494 (6.8%) | 10 (4.7%) | 79 (8.5%) |
p-value < 0.05 for Wilcoxon, or Chi2 (or Fisher exact) tests when applicable.
p-value < 0.05 for Cochrane-Armitage trend test.
For the BS2 and reference product groups, mean ages (SD) were 70.9 (12.4) and 70.6 (11.7) years, and the proportion male was 52.1 and 53.4%, mean BMI (SD) was 23.3 (4.0) and 23.3 (3.8) kg/m2, and the proportion of smokers was 31.8 and 34.3%, respectively. The CCI score in the 6 months prior to rituximab initiation was >3 for 76.9 and 72.8% of patients from the BS2 and reference product groups, respectively.
3.2.2. Hospital characteristics
Among NHL patients in the BS2 and reference product groups, 1280 and 7808 visits to the medicine department and 23 and 133 visits to the surgery department were documented, respectively (Supplementary Table S1). All except 6 (0.5%) and 152 (2.1%) patients with NHL from the BS2 and reference product groups received treatment in hospitals with >200 beds.
3.2.3. Treatment utilization patterns
Among BS2-treated NHL patients, 215 (18.7%) switched to BS2 after initiating treatment with the reference product (Table 2). The median (Q1, Q3) treatment follow-up duration was 118 (78, 153) days for BS2-prescribed patients and 89 (29, 130) days for reference product-prescribed patients (Figure 2). The median (Q1, Q3) treatment follow-up duration for BS-treated patients who switched from the reference product and for those without switching was 122 (98, 153) and 117 (71, 154) days, respectively (Supplementary Figure S5).
Figure 2.
Unadjusted Kaplan-Meier curves of treatment follow-up duration in non-Hodgkin lymphoma patients treated with rituximab. (A) Treatment follow-up duration for patients with Non-Hodgkin Lymphoma treated with Rituximab BS2. (B) Treatment follow-up duration for patients with Non-Hodgkin Lymphoma treated with Rituximab reference product. Lines 1 & 2 on the x-axis show the number of patients at risk in each group. Line 1 shows rituximab biosimilar patients, and Line 2 shows patients treated with rituximab reference product. Follow-up discontinuation is defined as ≥60 days without a treatment record.
BS2 utilization increased from 2019 to 2022 (p < 0.001), consistent with a decrease in the reference product prescription from 100% in 2019 to 55% in 2022 (p < 0.05, Supplementary Figure S4E). There was significantly more BS2 use vs. reference product use among larger (>499 beds) hospitals (Supplementary Table S1).
3.2.4. Concomitant treatment patterns among BS2-prescribed non-Hodgkin's lymphoma patients
The most common treatment combination with BS2 was alkylating agent + anthracycline + corticosteroid + vinca alkaloid (n = 163, 14.2%). Additional details about concomitant treatment patterns for BS2 NHL patients are described in Supplementary Table S4.
3.3. Trastuzumab in breast cancer & gastric cancer
3.3.1. Patient characteristics
We identified 8954 and 1609 patients with an ICD-10 code corresponding to BC or GC diagnosis and having at least one record of trastuzumab (reference product or BS) treatment (Table 3). Among BC patients, 333 (3.7%) received BS3 and 8621 (96.3%) received the reference product treatment. In total, 218 (65.5%) BS3-prescribed and 5898 (68.4%) reference product-prescribed BC patients had metastatic disease (Supplementary Figure S6).
Table 3.
Demographics and clinical characteristics of breast and gastric cancer patients treated with trastuzumab.
| Breast Cancer (N = 8954) | Gastric Cancer (N = 1609) | |||||||
|---|---|---|---|---|---|---|---|---|
| Biosimilar | Reference | Biosimilar Switch | Biosimilar No Switch | Biosimilar | Reference | Biosimilar Switch | Biosimilar No Switch | |
| N = 333 | N = 8621 | N = 96 (28.8%) | N = 237 (71.2%) | N = 59 | N = 1550 | N = 8 (13.6%) | N = 51 (86.4%) | |
| Age | ||||||||
| Mean (±SD) | 61.3 (±12.2) | 60.1 (±12.3) | 61.6 (±12.8) | 61.2 (±11.9) | 71.7 (±7.8) | 69.8 (±9.3) | 73 (±7.3) | 71.5 (±7.9) |
| Median | 62 | 60 | 62 | 62 | 72 | 71 | 73 | 72 |
| [Q1; Q3] | [52; 71] | [51; 69] | [52; 71] | [53; 71] | [67; 77] | [66; 76] | [70; 76.5] | [64; 77] |
| Age categories | ||||||||
| <40 | 18 (5.4%) | 378 (4.4%) | 5 (5.2%) | 13 (5.5%) | 0 (0.0%) | 16 (1.0%) | 1 (12.5%) | 13 (25.5%) |
| 40–64 | 174 (52.3%) | 4934 (57.2%) | 50 (52.1%) | 124 (52.3%) | 14 (23.7%) | 327 (21.1%) | 5 (62.5%) | 21 (41.2%) |
| 65–74 | 94 (28.2%) | 2227 (25.8%) | 27 (28.1%) | 67 (28.3%) | 26 (44.1%) | 711 (45.9%) | 1 (12.5%) | 16 (31.4%) |
| 75–84 | 44 (13.2%) | 953 (11.1%) | 12 (12.5%) | 32 (13.5%) | 17 (28.8%) | 463 (29.9%) | 1 (12.5%) | 1 (2.0%) |
| 85 ≤ | 3 (0.9%) | 129 (1.5%) | 2 (2.1%) | 1 (0.4%) | 2 (3.4%) | 33 (2.1%) | 1 (12.5%) | 1 (2.0%) |
| Gender | ||||||||
| Male | 0 (0.0%) | 30 (0.3%) | 0 (0.0%) | 0 (0.0%) | 46 (78.0%) | 1257 (81.1%) | 5 (62.5%) | 41 (80.4%) |
| Female | 333 (100%) | 8591 (99.7%) | 96 (100%) | 237 (100%) | 13 (22.0%) | 293 (18.9%) | 3 (37.5%) | 10 (19.6%) |
| Charlson Comorbidity Index categories | ||||||||
| [0; 2] | 129 (38.7%) | 3098 (35.9%) | 27 (28.1%)†,‡ | 102 (43%) | 10 (16.9%)† | 238 (15.4%) | 3 (37.5%) | 10 (19.6%) |
| [3; 5] | 82 (24.6%) | 2374 (27.5%) | 15 (15.6%) | 67 (28.3%) | 23 (39.0%) | 355 (22.9%) | 2 (25.0%) | 20 (39.2%) |
| 6 ≤ | 122 (36.6%) | 3149 (36.5%) | 54 (56.3%) | 68 (28.7%) | 26 (44.1%) | 957 (61.7%) | 3 (37.5%) | 21 (41.2%) |
| BMI | ||||||||
| Mean (±SD) | 23.5 (±3.8) | 23.4 (±5.1) | 23.9 (±3.9) | 23.3 (±3.7) | 21.8 (±3.5) | 22.5 (±3.3) | 22.2 (±3.6) | 21.7 (±3.5) |
| Median | 22.8 | 22.8 | 22.9 | 22.8 | 22 | 22.3 | 22.5 | 22.0 |
| [Q1; Q3] | [20.9; 25.8] | [20.5; 25.6] | [21.1; 26.4] | [20.9; 25.6] | [19.1; 23.9] | [20.1; 24.5] | [20.7; 24.5] | [18.6; 23.9] |
| Smoking status | ||||||||
| Yes | 57 (17.1%) | 1521 (17.6%) | 16 (16.7%) | 41 (17.3%) | 32 (54.2%) | 932 (60.1%) | 4 (50.0%) | 28 (54.9%) |
| No | 217 (65.2%) | 6118 (71.0%) | 71 (74%) | 146 (61.6%) | 20 (33.9%) | 502 (32.4%) | 3 (37.5%) | 17 (33.3%) |
| Missing | 59 (17.7%) | 982 (11.4%) | 9 (9.3%) | 50 (21.1%) | 7 (11.9%) | 116 (7.5%) | 1 (12.5%) | 6 (11.8%) |
p-value < 0.05 for Wilcoxon, or Chi2 (or Fisher exact) tests when applicable.
p-value < 0.05 for Cochrane-Armitage trend test.
The patient characteristics were similar between the BS3-prescribed and reference product-prescribed groups. Among the BS3-prescribed and reference product-prescribed BC patients, the mean (SD) age at trastuzumab initiation was 61.3 (12.2) and 60.1 (12.3) years, respectively. About half of the patients from BS3 and reference product groups were between 40 and 64 years of age at trastuzumab treatment initiation (52.3% and 57.2%, respectively). The mean (SD) BMI (23.5 [3.8] vs 23.4 [5.1] kg/m2) and percentage of smokers (17.1 vs 17.6%) were similar between BS3 and reference product groups. In total, 204 (61.2%) BS3-prescribed and 5,523 (64.0%) reference product-prescribed patients had CCI scores >3 in the 6 months prior to trastuzumab initiation.
In the GC setting, 59 (3.7%) patients received BS3 and 1,550 (96.3%) received the reference product treatment (Table 3). The mean (SD) age was 71.7 (7.8) for the patients from the BS3 group and 69.8 (9.3) years for those from the reference product group. Among the BS3 and reference product groups, 44.1 and 45.9% of patients were between 65 and 74 years of age at trastuzumab initiation, respectively. Overall, 78.0 and 81.1% of BS3-treated and reference product-treated patients were male. Among the BS3-precribed and reference product-prescribed patients, mean BMI (SD) was 21.8 (3.5) and 22.5 (3.3) kg/m2 and the proportion of smokers was 54.2% and 60.1%, respectively. In total, 83.1% BS3-prescribed and 84.6% reference product-prescribed patients had a CCI score >3 in the 6 months prior to trastuzumab initiation.
3.3.2. Hospital characteristics
Among BC patients who received BS3 and reference product treatment, 38 and 1,254 visits to the medicine department, and 328 and 8,149 visits to the surgery department were recorded, respectively (Supplementary Table S1). For GC patients who received BS3 and reference product treatment, and 44 and 933 visits to the medicine department, and 20 and 761 visits to surgery department were recorded, respectively (Supplementary Table S1). Only 290 (3.2%) BC patients (9 BS3-prescribed and 281 reference product-prescribed) and 102 (6.3%) GC patients (5 BS3-prescribed and 97 reference product-prescribed) were treated in hospitals with <200 beds.
3.3.3. Treatment utilization patterns
Among BS3 treated patients, 96 (28.8%) BC patients and 8 (13.6%) GC patients switched to BS3 after initiating treatment from with the reference product (Table 3). Among patients with BC, the median (Q1, Q3) duration of treatment was 343 (84, 448) days for the BS3 group and 156 (63, 343) days for the reference product group (Figure 3). Among patients with GC, the median (Q1, Q3) treatment follow-up duration was 182 (118, -) days for the BS3 group and 133 (46, 259) days for the reference product group (Figure 3). The median (Q1, Q3) treatment follow-up duration for BS-treated patients who switched from the reference product and for those without switching was 377 (126, 714) and 336 (77, 374) days for BC, and 179 (132, Not estimable) and 187 (86, Not estimable) days for GC, respectively (Supplementary Figure S7).
Figure 3.
Unadjusted Kaplan-Meier curves of treatment follow-up duration in patients treated with trastuzumab. (A & B) In breast and (C & D) gastric cancer. Lines 1 and 2 on the x-axis show the number of patients at risk in each group. Line 1 shows trastuzumab biosimilar (BS) patients, and Line 2 shows patients treated with trastuzumab reference (Ref) product. Follow-up discontinuation is defined as ≥60 days without a treatment record.
BS3 utilization significantly increased from 2019 to 2022 (p < 0.001), and there was significantly more BS3 use vs. reference product use among larger (>499 beds) hospitals (p < 0.05) (Supplementary Figure S4C & D).
3.3.4. Concomitant treatment patterns among BS3-prescribed patients
The most common treatment combination with BS3 was monoclonal antibody + taxane in BC (n = 107, 32.1%) and antimetabolite antineoplastic + platinum-containing antineoplastic in GC (n = 41, 69.5%). Additional details about concomitant treatment patterns for BS3 in BC and GC patients are described in Supplementary Tables S5 & S6.
4. Discussion
Using Japanese hospital administrative data, we identified patients with at least one claim of bevacizumab BS-Pfizer (bevacizumab BS1), rituximab BS-Pfizer (rituximab BS2), or trastuzumab BS-Pfizer (trastuzumab BS3) or the corresponding reference products between 1 January 2019 and 30 June 2022 for the approved indications to provide far-ranging insights into BS use in the real world in Japan. Among the cohorts formed by this approach, we found that the characteristics of patients treated with BS were similar to those treated with corresponding reference products with regard to age, gender, CCI, smoking status and other factors. There were a few cases of differences between groups, such as age and CCI distribution in CRC patients treated with bevacizumab, CCI distribution among NHL patients treated with rituximab and CCI distribution among gastric cancer patients treated with trastuzumab that were able to be detected due to the large sample sizes. Looking comprehensively across the measured patient characteristics, it appears that BS patients have comparable attributes relative to their reference product-treated counterparts in the sample.
Though biosimilars are noted in Japanese treatment guidelines [39–44], we found that BS uptake was limited over the study horizon. Nonetheless, there was a significant trend in increasing use over time, with a greater proportion of patients receiving BS in each successive year of the analysis. In the latest period observed (first half of 2022), BS constituted 30, 30, 45, 12 and 10% of the CRC, NSCLC, NHL, BC and GC indication cohorts, respectively. Over the study period, we saw the greatest annual gains in proportion using BS among bevacizumab-treated NSCLC (3% BS use in 2020 to 30% in 2022) and rituximab-treated NHL (12% BS use in 2020 to 45% in 2022). Trastuzumab use in BC and GC was the most limited over the study period and reached a peak of <20% in 2022. The limited uptake of biosimilars relative to the USA and countries in the European Union is likely due to the later entry of biosimilars in Japan, as well as unique Japanese regulatory and market conditions that have posed similar challenges to uptake of small-molecule generics [45].
We observed that switches from reference products to BS occurred in between 14 and 39% of the patient cohorts treated with BS, with the largest proportions of switching in bevacizumab in CRC (39%) and NSCLC (29%), and trastuzumab in BC (29%). Accordingly, the majority of included patients that received BS therapy initiated their regimen with the same BS. Evaluation of the sub-group that did switch to a BS relative to those who initiated therapy on a BS confirmed the similar characteristics of the switching sub-group to the no switch sub-group on most measured variables in most indications. We observed a significantly lower CCI distribution among bevacizumab switchers in NSCLC, and significantly higher CCI among rituximab switchers in NHL and trastuzumab switchers in BC; however, it is not possible to assess the association between switching to BS and CCI since our descriptive study does not take into account other potential variables. In rituximab in NHL, those who switched also had significantly younger age distribution than the no switch patients. These findings can inform future hypothesis-driven research to elucidate the factors associated with switching to BS in cancer patients in Japan.
We also analyzed use of BS relative to reference products by hospital size, to explore if hospital size (as measured by count of beds) may influence use of BS, given differences in patient volume in the cancers of interest and associated familiarity with evolving therapeutic options in each tumor type. Although we observed significantly less use of BS in larger hospitals (>500 beds) among patients treated with bevacizumab in CRC and NSCLC and trastuzumab in BC and GC, and more use of BS in larger hospitals among patients treated with rituximab for NHL, establishing an association between hospital size and use of BS should be interpreted with caution since other variables could impact this relationship and were beyond the scope of this descriptive study. These patterns of care warrant further investigation in future studies to better understand the factors driving differential use by hospital size.
In analyses of treatment follow-up duration, we assessed BS and reference product groups to obtain initial exploratory insights intended to generate hypotheses. Specifically, we used Kaplan-Meier analysis to explore the time until a gap of 60 days or longer without receipt of the monoclonal antibody of interest as a proxy for the end point of progression-free survival (PFS) in the absence of an exact treatment end date [42]. In these unadjusted exploratory analyses, we found numerically longer median duration of treatment follow-up for the BS groups relative to the reference product groups. However, it should be noted that these analyses were not adjusted for potential confounders, and there are many important potential variables that are not captured in MDV such as disease severity, treatment-related adverse events, reasons for switching and outpatient death. In addition, it should be considered that a time-related bias due to switching could affect the treatment follow-up analysis for the BS group and the reference group. As such, we focused the findings reported here on median and interquartile range results and interpret the overlap in these ranges as evidence supportive of equivalent outcomes as in each respective BS pivotal clinical trial [8,10,12,13]. Future studies should more rigorously assess the real-world comparative effectiveness of the BS relative to their reference products, including direct assessment of toxicity, progression/event-free survival and overall survival and adjustment for potential confounders such as age, comorbidities, cancer stage and grade and concomitant therapies.
The MDV database used in our study includes a representative population and collects data from all insurance types related to anonymized outpatient, inpatient and DPC data [46]. The analyzed demographic characteristics of the patient population are consistent with those of the Japanese patients with CRC [47], NSCLC [48], NHL [49,50], BC [51] and GC [52] reported in previous studies. However, as MDV only captures records from participating hospitals and does not capture medical care provided in other clinical settings, there is a potential of underestimation of some variables. Other clinical measures, such as cancer grade and Eastern Cooperative Oncology Group performance status (ECOG PS) that are not captured in MDV, may differ among these patient groups, and warrant further studies.
This study has several limitations that should be noted. The MDV hospital-based claims database has missing data for some variables and is subject to misclassification of cancer stage. In addition, MDV lacks detailed diagnosis and prognosis data (histology, ECOG PS, disease severity, etc.) and clinical outcome information, does not capture deaths that occur outside the hospital and lacks clinical notation to explain things like reasons for switching to/from biosimilars. The MDV database does not merge data from an individual patients receiving treatment at more than one hospital, and so duplicate records can be difficult to identify [43]. For these reasons, we restricted the scope of this study to descriptive analyses that utilized established MDV variables and did not perform efficacy or safety analyses. Nonetheless, our descriptive findings provide important initial insights into the use of oncology BS in Japan and can serve as a foundation for future research. It is also important to note that we focused on a comparison between bevacizumab Pfizer BS, rituximab Pfizer BS and trastuzumab Pfizer BS and their respective reference products, but additional biosimilars to these reference products also exist. Future research should conduct similar analyses of alternative biosimilars to inform stakeholders about patient characteristics, treatment duration and reasons for switching to/from biosimilar therapy. Last, we explored a wide range of patient, provider and treatment pattern characteristics in our study design, but some outcomes were not explored due to the need to limit study scope. For example, cost of care is available in the MDV, but we decided not to explore cost outcomes in this study because PDMA guidance notes that biosimilars are typically priced at approximately 30% less than reference products, so treatment cost-savings of a commensurate scale are expected. Additionally, introducing inclusion of cost outcomes, with appropriate exploration of sub-group outcomes, would add dozens of additional outcomes to this already far-ranging study. We believe that future research is warranted exploring Japan's real-world cost savings with use of oncology biosimilars vs. reference products, but this would be better served as a stand-alone study design.
5. Conclusion
To our knowledge, this is the first analysis of real-world oncology BS use in Japan. Our descriptive analyses provide important insights about similarity in characteristics between patients treated with biosimilars and reference products to date in Japan, characteristics of patients who switch to biosimilars versus those who initiate therapy with biosimilars, the most prevalent concomitantly administered classes of therapies with biosimilars, trends in biosimilar market share, and differences in biosimilar use by hospital size. Future hypothesis-driven research should build on our findings and evaluate additional end points such as response, survival, cost of care and patient-reported outcomes to further advance the evidence base for oncology biosimilars in Japan.
Supplementary Material
Funding Statement
The study was sponsored by Pfizer Inc. JA Roth, A Shelbaya, S Dorman and C Ono hold stock in Pfizer Inc. M Rahshenas, N Masurkar and G Nowacki were compensated as consultants for Pfizer Inc.
Supplemental material
Supplementary data for this article can be accessed at https://doi.org/10.1080/14796694.2024.2352405
Author contributions
Design of study: JA Roth, M Rahshenas, G Nowacki, N Masurkar, A Shelbaya, K Tajima, S Dorman and C Ono; acquisition of data: M Rahshenas, G Nowacki, A Shelbaya, K Tajima, C Ono; analysis of data: JA Roth, M Rahshenas, G Nowacki, N Masurkar, A Shelbaya, K Tajima, S Dorman and C Ono; interpretation of data: JA Roth, M Rahshenas, G Nowacki, N Masurkar, A Shelbaya, K Tajima, S Dorman and C Ono; drafting manuscript: JA Roth, M Rahshenas, G Nowacki, N Masurkar, A Shelbaya, K Tajima, S Dorman and C Ono; final approval of manuscript: JA Roth, M Rahshenas, G Nowacki, N Masurkar, A Shelbaya, K Tajima, S Dorman and C Ono.
Financial disclosure
The study was sponsored by Pfizer Inc. JA Roth, A Shelbaya, S Dorman and C Ono hold stock in Pfizer Inc. M Rahshenas, N Masurkar and G Nowacki were compensated as consultants for Pfizer Inc. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.
Competing interests disclosure
JA Roth, A Shelbaya, K Tajima, S Dorman and C Ono are employees of Pfizer Inc. M Rahshenas, N Masurkar and G Nowacki are employees of Oracle Life Sciences. The authors have no other competing interests or relevant affiliations with any organization or entity with the subject matter or materials discussed in the manuscript apart from those disclosed.
Writing assistance
No writing assistance was utilized in the production of this manuscript.
Ethical conduct of research
All data used in this study were anonymized by Medical Data Vision Co., Ltd. This observational study was performed in accordance with ethical principles consistent with the Ethical Guidelines for Biomedical Research Involving Human Subjects, the Declaration of Helsinki and the Japanese Act on the Protection of Personal Information. According to the Japanese Ethical Guidelines for Medical and Health Research Involving Human Subjects, institutional review board approval and patient informed consent were not required for this observational study as it used secondary data without any identifiable patient information.
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