Trends of Strong and Weak Opioid Prescriptions in Japan: A Cross-Sectional Study Based on Open Data from the National Database and Hospital Claims Data from Fiscal Years 2015 to 2021

Abstract

Trends in opioid use for patients with cancer in Japan remain unclear. This study investigated the prescription trends of strong and weak opioids in Japan and the prescription trends among patients with or without support from a palliative care team. Open data from the National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB) and administrative claims data from the University of Yamanashi Hospital from fiscal years 2015 to 2021 were used. Opioid consumption was reported using the defined daily dose (DDD) per 1000 inhabitants per day (DID) and DDD per 100 bed-days. The NDB open data showed a decrease from 0.3111 to 0.2271 in the DID for inpatients (p = 0.0001) and an increase from 0.5971 to 0.8597 in the DID for outpatients (p = 0.0003). Consumption of tramadol, a weak opioid, increased in both inpatient and outpatient settings. In University of Yamanashi Hospital, the annual percentage of opioid consumption changed little among strong opioids (98.1–97.1%) and weak opioids (1.8–2.8%) for patients supported by a palliative care team (p = 0.2842), but changed more noticeably among strong opioids (86.6–69.6%) and weak opioids (13.3–30.3%) for patients without support from a palliative care team (p < 0.001). Opioid prescription patterns in Japan changed during the 7-year study period, which indicated shifts in the types of opioids used. Additionally, the trend in opioid prescriptions was characterized by the presence or absence of palliative care team support.

INTRODUCTION

Opioid analgesics are the mainstay of pain management for a variety of pain conditions, including cancer, chronic, and postoperative pain.¹⁾ Globally, opioid overuse is a concern, and its use has increased significantly in the United States of America and other developed countries during the past decade,²⁾ although opioid consumption in Japan has been lower than that in other countries.³⁾ Since 2007, the policies of the Cancer Control Act have promoted opioid use in patients with cancer in Japan.⁴⁾ The Ministry of Health, Labor and Welfare (MHLW) in Japan has been reporting the annual use of morphine, fentanyl, and oxycodone; however, there are no regular reports on the use of other opioids.⁵⁾ Furthermore, for some drugs, such as antimicrobials, aggregate results using a standardized index called the defined daily dose (DDD) are provided,⁶⁾ but not for opioids.

A meta-analysis comprising 52 studies revealed that 64% of patients with metastatic, advanced, and terminal-stage cancer, 59% of patients who received anticancer treatment, and 33% of patients cured of cancer reported pain complaints. These findings underscore the significant impact of pain on the QOL of patients with cancer.⁷⁾ Moreover, according to a survey by the MHLW in 2022, 42.8% of Japanese people with a terminal disease prefer to spend their final days at home.⁸⁾ Therefore, opportunities for opioid use are expected to increase in Japan’s aging society; however, the actual situation remains unclear.

The WHO Cancer Pain Management Guidelines, revised in 2018, expanded the indications for strong opioids to include mild-to-moderate cancer pain in addition to traditional moderate-to-severe cancer pain.⁹⁾ Weak opioids are used to treat mild-to-moderate pain. However, there are few reports in Japan about the use of strong vs. weak opioids, particularly by patients with cancer who are not in the terminal stages of their disease.

Palliative care teams, which comprise physicians, nurses, pharmacists, and other healthcare professionals, began providing specialized palliative care in Japanese hospitals in 2002.¹⁰⁾ A previous study conducted at a university hospital in Spain reported an increased use of opioids after a palliative care team was established.¹¹⁾ Furthermore, another study reported that patients with cancer who were terminally ill and received supportive care from a palliative care team were more frequently prescribed new opioids.¹²⁾ However, these teams support patients not only during the terminal phase but also during the treatment phase. Furthermore, the trend of opioid prescriptions among patients with and without palliative care team support is not clear.

The purpose of this study was to identify, based on DDD, trends of opioid prescriptions in inpatient and outpatient settings in Japan, and opioid prescriptions among patients with or without support from a palliative care team.

MATERIALS AND METHODS

Study Design and Data Sources

This cross-sectional study utilized data from the National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB) open data¹³⁾ and the administrative claims and discharge summary data were based on diagnostic procedure combination (DPC) data¹⁴⁾ from the University of Yamanashi Hospital. The NDB open data used in this study were obtained from the MHLW published receipt information and specific medical examination information database, which contains the top 100 prescribed drugs in each efficacy category. The actual prescription quantities for products with <1000 prescriptions for oral and topical drugs and <400 prescriptions for injectable drugs were anonymized. Payment information was recorded in the DPC data according to the diagnosis group classification, with basic patient information, including age, disease, diagnosis group classification (International Classification of Diseases, 10th Revision [ICD-10]), operation type, and medical treatment (drugs, date, frequency, quantity, and tests). The survey period spanned 7 years, from fiscal years (FYs) 2015 to 2021.

Opioid Analgesics and Defined Daily Dose

The target opioid dosage forms of morphine, fentanyl, oxycodone, hydromorphone, tapentadol, methadone, codeine, and tramadol were included in the NDB open data and DPC data analyses. We classified the opioids into weak and strong potency categories according to the WHO 3-step analgesic ladder.^15,16) In Japan, oral and injectable forms of hydromorphone were launched as new opioid products in 2017–2018. DDD, proposed by the WHO, is a unit of measurement commonly used in drug consumption studies that allows standardization and comparison of drug use in different formulations and doses¹⁷⁾; thus it is beneficial for assessing drug use. The DDD of the target opioids was determined using the Anatomical Therapeutic Chemical/DDD index 2023.¹⁸⁾ Opioids for which a WHO DDD was not defined were added based on previous studies.

Study Patients

Using the DPC data, we evaluated the discharged patients from the hospital during the study period as follows: men and women of all ages with a malignancy code (ICD-10 codes: C00–C97) for either the primary disease, the reason for admission, or the injury or disease that invested the most medical resources, and who had received at least 1 prescription of an opioid for analysis during hospitalization. Patients with multiple malignancy diagnoses were prioritized in the order of “primary disease,” “reason for admission,” and “injury or disease that invested the most medical resources.” The FY to which each patient belonged was used as the FY at the time of admission.

Measurement of Drug Utilization

Opioid drug use was evaluated using the DDD per 1000 inhabitants per day (DID) and DDDs per 100 bed-days. From the NDB open data, we calculated the DID by categorizing them according to the medical institution. Medical institutions from which the prescriptions originated were divided into outpatient and inpatient receipts. The number of opioids prescribed to eligible patients during the study period was tabulated in the DPC data. Opioid prescriptions on the day of the surgery and outpatient prescriptions were excluded from the analyses. The DID (Formula 1) and DDDs per 100 bed-days (Formula 2) were calculated for each year based on the aggregated prescription volume.

  

$$\begin{array}{l}\text{DID\hspace{0.17em}}\left(\text{DDDs}/1000\text{\hspace{0.17em}inhabitants}/\text{d}\right)=\text{opioid\hspace{0.17em}consumption}\\ \left(\text{g}\right)/\text{DDD\hspace{0.17em}}\left(\text{g}\right)/\left(\text{population}/1000\text{\hspace{0.17em}inhabitants}\right)/365\left(\text{d}\right)\end{array}$$(1)

  

$$\begin{array}{l}\text{DDDs}/100\text{\hspace{0.17em}bed-days}=\left(\text{opioid\hspace{0.17em}consumption\hspace{0.17em}}\left[\text{g}\right]\times 100\right)/\\ \left(\text{DDD\hspace{0.17em}}\left[\text{g}\right]\times \text{total\hspace{0.17em}hospital\hspace{0.17em}days}\right).\end{array}$$(2)

Additionally, we calculated the amount of each opioid consumed using the percentage of DDDs/100 bed-days from the DPC data by dividing eligible patients with or without support from a palliative care team. The activities of the palliative care team at the University of Yamanashi Hospital are initiated upon request from the medical staff, which includes the attending physician team, to provide patient support regardless of the degree of the patient’s pain.

Statistical Analyses

For the statistical analyses, nominal variables were calculated as percentages. The median (interquartile range) was calculated for continuous variables. A linear regression analysis was used to calculate trends in opioid consumption. Trends in the proportion of strong and weak opioids prescribed with and without support from a palliative care team during the study period were assessed using the Cochran–Armitage trend test. Statistical significance was set at p < 0.05.

All statistical analyses were performed using the Statistical Analysis System 9.4 (SAS Institute, Cary, NC, U.S.A.).

Ethics Statement

This study was approved by the Ethical Review Committee of the University of Yamanashi Hospital (Reception No. 2687) and was conducted in accordance with the Declaration of Helsinki. The requirement for informed consent was waived owing to the retrospective study design.

RESULTS

Opioid Consumption in Japan from NDB Open Data

Table 1 shows the opioids and DDDs analyzed in this study. The DDD of injectable fentanyl was not defined. The potency of fentanyl for injection is as potent as 1/100 of that of oral morphine, according to a previous report.¹⁹⁾ Therefore, the DDD of injectable fentanyl was defined as 0.001 in this study. The DID for opioid consumption from the NDB open data is presented in Table 2. The DID assessment over time decreased from 0.3111 to 0.2271 for inpatients (p = 0.0001) and increased from 0.5971 to 0.8597 for outpatients (p = 0.0003). The tramadol dose increased from 0.0158 to 0.0239 DID in the inpatient setting (p = 0.0194) and from 0.1716 to 0.4233 DID in the outpatient setting (p = 0.0009).

Table 1. List of Target Opioids

Administration route	Category	Name	WHO ATC code	DDD (g)a)
Oral preparations	Strong	Morphine	N02AA01	0.1
Oral preparations	Strong	Fentanyl	N02AB03	0.0006
Oral preparations	Strong	Oxycodone	N02AA05	0.075
Oral preparations	Strong	Methadone	N07BC02	0.025
Oral preparations	Strong	Tapentadol	N02AX06	0.4
Oral preparations	Strong	Hydromorphone	N02AA03	0.02
Oral preparations	Weak	Codeine	N02AA59	0.1
Oral preparations	Weak	Tramadol	N02AX02	0.3
Parenteral preparations	Strong	Morphine	N02AA01	0.03
Parenteral preparations	Strong	Fentanyl	N02AB03	0.001*
Parenteral preparations	Strong	Oxycodone	N02AA05	0.03
Parenteral preparations	Strong	Hydromorphone	N02AA03	0.004
Rectal preparations	Strong	Morphine	N02AA01	0.03
Transdermal preparations	Strong	Fentanyl	N02AB03	0.0012

a) Used by ATC/DDD index 2023. * Scholten¹⁹⁾ ATC, anatomical therapeutic chemical; DDD, defined daily dose.

Table 2. Inpatient and Outpatient Opioid Trends in the National Database as DID

	2015	2016	2017	2018	2019	2020	2021	Slope	95% CI	p-Value
Inpatient total	0.3111	0.3051	0.2948	0.2800	0.2702	0.2417	0.2271	−0.01441	−0.01776 to –0.01106	0.0001
Morphine	0.0393	0.0374	0.0337	0.0297	0.0266	0.0222	0.0201	−0.00340	−0.00372 to –0.00307	< 0.0001
Fentanyl	0.2036	0.1958	0.1839	0.1697	0.1595	0.1429	0.1346	−0.01205	−0.01313 to –0.01097	<0.0001
Oxycodone	0.0482	0.0481	0.0501	0.0471	0.0436	0.0368	0.0317	–0.00280	–0.00453 to –0.00107	0.0088
Methadone	0.0004	0.0006	0.0008	0.0007	0.0009	0.0009	0.0009	0.00008	0.00003 to 0.00013	0.0068
Tapentadol	0.0007	0.0008	0.0007	0.0010	0.0013	0.0013	0.0012	0.00011	0.00004 to 0.00017	0.0072
Hydromorphone	—	—	0.0005	0.0058	0.0121	0.0129	0.0129	0.00271	0.00157 to 0.00385	0.0017
Codeine	0.0031	0.0031	0.0028	0.0026	0.0025	0.0020	0.0019	−0.00021	−0.00027 to –0.00016	0.0002
Tramadol	0.0158	0.0193	0.0223	0.0234	0.0238	0.0227	0.0239	0.00115	0.00028 to 0.00203	0.0194
Outpatient total	0.5971	0.6797	0.7273	0.7663	0.7850	0.8017	0.8597	0.03890	0.02807 to 0.04974	0.0003
Morphine	0.0297	0.0302	0.0290	0.0280	0.0260	0.0293	0.0283	−0.00033	−0.00097 to 0.00032	0.2491
Fentanyl	0.2528	0.2502	0.2424	0.2334	0.2294	0.2396	0.2476	−0.00178	−0.00592 to 0.00237	0.3205
Oxycodone	0.0917	0.0937	0.0947	0.0949	0.0916	0.0913	0.0932	−0.00012	−0.00091 to 0.00067	0.7098
Methadone	0.0008	0.0011	0.0016	0.0019	0.0023	0.0028	0.0031	0.00040	0.00036 to 0.00043	<0.0001
Tapentadol	0.0016	0.0021	0.0023	0.0031	0.0044	0.0052	0.0057	0.00073	0.00056 to 0.00090	0.0001
Hydromorphone	—	—	0.0007	0.0068	0.0190	0.0271	0.0332	0.00615	0.00387 to 0.00843	0.0010
Codeine	0.0488	0.0463	0.0427	0.0408	0.0382	0.0259	0.0252	−0.00416	−0.00560 to –0.00271	0.0007
Tramadol	0.1716	0.2561	0.3140	0.3573	0.3740	0.3805	0.4233	0.03801	0.02399 to 0.05205	0.0009

The slope, 95% CI, and p-value for the trend in opioid consumption were calculated using linear regression analysis. DID, DDDs/1000 inhabitants/d; DDD, defined daily dose; CI, confidence interval; Bold represents items with p < 0.05.

Opioid Consumption in a Single Center from DPC Data

As presented in Fig. 1, 26357 patients were diagnosed with malignancy, and 2840 patients (10.8%) were prescribed opioids during the study period. Among them, 1162 patients (4.4%) had palliative care team support. As listed in Table 3, 1704 patients (60.0%) were men, with a median age of 67 years. A total of 804 patients (28.3%) had gastrointestinal organ malignancies, which were the most frequently observed in this study. The median length of the hospital stay was 17 d. As depicted in Table 4, no significant increase was observed in total opioid consumption, measured as DDDs/100 bed-days from FYs 2015 to 2021 (50.4–63.2, p = 0.2699). However, tramadol consumption increased (1.9–7.5, p = 0.0032).

Fig. 1. Flowchart Showing the Study Participant Selection Process

Table 3. Study Population Characteristics of a Single Center from the DPC Data

	Total	2015	2016	2017	2018	2019	2020	2021
Diagnosed with cancer (n)	26357	2885	3276	3688	4158	4128	3941	4281
Diagnosed with cancer and prescribed opioids (n, %)	2840 (10.8)	353 (12.2)	368 (11.2)	418 (11.3)	427 (10.3)	369 (8.9)	437 (11.1)	468 (10.9)
Sex (male, %)	1704 (60.0)	227 (64.3)	239 (64.9)	229 (54.8)	233 (54.6)	232 (62.9)	276 (63.2)	268 (57.3)
Age, median (Q1–Q3, years)	67 (58–74)	64 (57–73)	67 (59–74)	66 (56–73)	67 (58.5–74)	68 (59–74)	69 (59–74)	69 (59–75)
Age (years) (n, %)
0–9	4 (0.1)	1 (0.3)	2 (0.5)	0 (0)	0 (0)	0 (0)	1 (0.2)	0 (0)
10–19	10 (0.4)	3 (0.8)	2 (0.5)	0 (0)	0 (0)	0 (0)	3 (0.7)	2 (0.4)
20–29	28 (1.0)	7 (2.0)	7 (1.9)	1 (0.2)	5 (1.2)	2 (0.5)	0 (0)	6 (1.3)
30–39	77 (2.7)	29 (8.2)	2 (0.5)	14 (3.3)	11 (2.6)	8 (2.2)	8 (1.8)	5 (1.1)
40–49	237 (8.3)	81 (22.9)	24 (6.5)	55 (13.2)	28 (6.6)	19 (5.1)	13 (3.0)	17 (3.6)
50–59	571 (20.1)	102 (28.9)	58 (15.8)	77 (18.4)	76 (17.8)	64 (17.3)	95 (21.7)	99 (21.2)
60–69	822 (28.9)	99 (28.0)	127 (34.5)	119 (28.5)	144 (33.7)	116 (31.4)	111 (25.4)	106 (22.6)
70–79	801 (28.2)	31 (8.8)	106 (28.8)	116 (27.8)	108 (25.3)	111 (30.1)	148 (33.9)	181 (38.7)
80–89	273 (9.6)	0 (0)	38 (10.3)	34 (8.1)	50 (11.7)	45 (12.2)	56 (12.8)	50 (10.7)
≥90	17 (0.6)	0 (0)	2 (0.5)	2 (0.5)	5 (1.2)	4 (1.1)	2 (0.5)	2 (0.4)
Cancer site (n, %)
Gastrointestinal organs	804 (28.3)	78 (22.1)	103 (28.0)	103 (24.6)	124 (29.0)	129 (35.0)	124 (28.4)	143 (30.6)
Lung	431 (15.2)	43 (12.2)	59 (16.)	63 (15.1)	58 (13.6)	32 (8.7)	75 (17.2)	101 (21.6)
Lip and pharynx	281 (9.9)	31 (8.8)	32 (8.7)	37 (8.9)	37 (8.7)	42 (11.4)	44 (10.1)	58 (12.4)
Female genital organs	264 (9.3)	36 (10.2)	31 (8.4)	52 (12.4)	58 (13.6)	26 (7.0)	33 (7.6)	28 (6.0)
Blood	225 (7.9)	43 (12.2)	25 (6.8)	34 (8.1)	29 (6.8)	27 (7.3)	32 (7.3)	35 (7.5)
Renal and urinary tract	216 (7.6)	32 (9.1)	18 (4.9)	33 (7.9)	24 (5.6)	27 (7.3)	51 (11.7)	31 (6.6)
Male genital organs	132 (4.6)	29 (8.2)	20 (5.4)	16 (3.8)	12 (2.8)	18 (4.9)	19 (4.3)	18 (3.8)
Others	487 (17.1)	61 (17.3)	80 (21.7)	80 (19.1)	85 (19.9)	68 (18.4)	59 (13.5)	54 (11.5)
Length of hospital stay, median (Q1–Q3, d)	17 (8–34)	20 (9–41)	22 (10–41.5)	21 (9–38)	15 (7–28)	18 (9–37)	14 (6–29)	14 (7–28)

DPC, diagnostic procedure combination.

Table 4. Trends in Opioid DDDs in a Single Center from the DPC Data as DDDs/100 Bed-Days

	2015	2016	2017	2018	2019	2020	2021	Slope	95% CI	p-Value
Total	50.4	36.1	39.0	62.0	41.0	49.9	63.2	2.4	−2.61 to 7.47	0.2699
Morphine	17.6	4.5	8.5	12.2	5.7	9.2	9.3	−0.7	−2.83 to 1.52	0.4749
Fentanyl	21.0	20.0	16.4	22.6	15.1	17.5	28.2	0.6	−1.74 to 2.83	0.5661
Oxycodone	8.5	6.7	6.8	8.8	7.4	7.1	5.7	−0.3	−0.75 to 0.24	0.2470
Methadone	0.3	0.0	1.3	1.0	1.0	1.3	0.7	0.1	−0.16 to 0.30	0.4444
Tapentadol	0.4	1.7	1.5	2.9	1.2	1.3	1.9	0.1	−0.26 to 0.50	0.4584
Hydromorphone	—	—	1.4	10.8	5.5	4.8	8.8	0.9	−3.03 to 4.82	0.5196
Codeine	0.8	0.5	0.1	0.6	0.7	0.6	1.2	0.1	−0.08 to 0.23	0.2724
Tramadol	1.9	2.7	3.2	3.4	4.5	8.2	7.5	1.0	0.53 to 1.55	0.0032

The slope, 95% CI, and p-value for the trend in opioid consumption were calculated using linear regression analysis. CI, confidence interval; DDD, defined daily dose; DPC, diagnostic procedure combination; Bold represents items with p < 0.05.

Figure 2 illustrates the percentages of strong and weak opioid consumption with and without support from a palliative care team. Supplementary Tables S1 and S2 list the detailed data. The annual percentage of opioid consumption changed among strong opioids (86.6–69.6%) and weak opioids (13.3–30.3%) in patients without support from a palliative care team from FYs 2015 to 2021 (p < 0.001). The annual percentage of tramadol use in patients without support from a palliative care team increased from 11.3% in FY 2015 to 27.3% in FY 2021 (p = 0.0047). The annual percentage of opioid consumption changed among strong opioids (98.1–97.1%) and weak opioids (1.8–2.8%) for patients with support from a palliative care team (p = 0.2842). The annual percentage of hydromorphone use in patients with support from a palliative care team increased from 2.7% in FY 2017 to 21.2% in FY 2021 (p = 0.4012).

Fig. 2. Percentages of Strong and Weak Opioid Consumption with and without Supported from a Palliative Care Team in a Single Center from the DPC Data

DPC, diagnostic procedure combination.

DISCUSSION

This study investigated trends in opioid-prescribing intensity in Japan using DID based on NDB open data. In addition, the single-center DPC data revealed trends in opioid consumption in patients with and without support from a palliative care team. The NDB covers more than 126 million individuals’ electronic claims data annually, including data from 99% of hospitals. The NDB open data, which the MHLW began providing in 2016, was created by aggregating a portion of the NDB data, excluding any sensitive or private information. Thus, researchers using it do not have access to facility- or patient-level information. The DPC is a case-mix patient classification system initiated by the MHLW in 2002 and is linked to the per-diem payment system. The DPC database contains administrative claims and discharge abstracts for individual patients.²⁰⁾ Previous validation studies have shown that the sensitivity and specificity of the diagnosis and procedure records in the database are good, and the validity of the cancer diagnosis is high.²¹⁾ The methodology in this study was useful for the continued assessment of opioid use and changes.

Opioid consumption among inpatients decreased during the study period, whereas opioid consumption among outpatients increased (Table 2). Moreover, in FY 2021, opioid use in outpatients was 3.7 times higher than that in inpatients. According to a report by the MHLW, the estimated number of patients with cancer in Japan in 2020 was 1.6 times higher among outpatients than inpatients, with the proportion of outpatients increasing over time.^22–24) Hence, the number of patients requiring opioids in outpatient settings is expected to rise. Suzuki et al.²⁵⁾ reported that community pharmacists have contributed to the reduction of inappropriate prescribing in opioid-using patients in a nationwide survey. In addition, opioid stewardship has recently emerged, modeled after antimicrobial stewardship, and focuses on the management of opioids.²⁶⁾ To promote the appropriate use of opioids, it is essential for pharmacists with expertise, community pharmacists, and board-certified palliative pharmacists to take further action by controlling dosages and evaluating adverse effects.

In this study, the DID for morphine in FY 2020 was 0.0293 (Table 2). The DID was 1.4 in Canada in 2020²⁷⁾ and 1.4 in Australia in 2014.²⁸⁾ Morphine consumption in Japan is lower than that in other countries. Previous reports have indicated that Japan prescribes fewer opioids than the United States of America.²⁹⁾ The use of the DID to study opioid consumption allows for comparison with other countries. As previous studies have conducted longitudinal evaluations,^30,31) conducting such a study in Japan over time is necessary.

Single-center inpatient data showed that the use of opioids increased from FYs 2015 to 2021, which was possibly attributed to an increase in the number of patients prescribed opioids and the number of opioid prescription days. The number of patients diagnosed with malignancies in hospitals increased from 2885 in FY 2015 to 4281 in FY 2021, a 1.5-fold increase (Table 3). The number of patients with opioid prescriptions increased from 353 to 468, which can be inferred as a contributing factor to the increase in DDDs/100 bed-days (Table 3). The rise in tramadol use, a weak opioid, may be attributed to the WHO guidelines, revised in 2018, which expanded the indications for weak opioids.⁹⁾ Tramadol is not designated as a narcotic in Japan and is easier to prescribe than other strong opioids.

Tramadol consumption significantly increased in patients without support from a palliative care team. In contrast, the prescription of strong opioids such as hydromorphone tended to increase, although the difference was not statistically significant among patients with support from a palliative care team. Dzierzanowski and Kozlowski³²⁾ examined opioid-prescribing trends between palliative and non-palliative care physicians in 2022 and reported that palliative care physicians used a variety of strong opioids, while non-palliative care physicians most often used tramadol. They stated that this is because palliative care physicians are well trained and well prepared to prescribe opioids, while non-palliative care physicians tend to be hesitant to prescribe strong opioids for fear of making prescribing errors. Furthermore, this study’s results suggest that consumption of newly released opioids tends to increase in patients with support from a palliative care team. Takahashi et al.¹²⁾ reported that terminally ill patients with cancer supported by a palliative care team had an increased frequency of prescriptions for newly released opioids. This may be because physicians and pharmacists on the palliative care team in Japan have a broad knowledge of opioid pharmacotherapy,³³⁾ including newer opioids, because of their educational position on opioid pharmacotherapy. The other reason is that previous recommendations suggested starting treatment with non-opioid analgesics for cancer pain according to the analgesic ladder.³⁴⁾ However, the WHO guideline was revised in 2018 and advocates for the use of weak and strong opioids, with or without non-opioid analgesics, depending on the patient's cancer pain level.⁹⁾ This may have led to an increase in the use of strong opioids by palliative care physicians.

LIMITATIONS

This study had several limitations. First, NDB open data were used. However, drugs with fewer than the minimum aggregate units of prescriptions were excluded, which potentially resulted in an underestimation of opioid use in Japan. Second, some opioids were possibly used for chronic pain rather than cancer pain; however, a distinction between them could not be made because data on the reasons for prescribing were not available in the DPC data. Third, this study did not consider the degree of pain. Therefore, it is uncertain to what extent the patients with or without support from a palliative care team had pain from cancer. Finally, the limited number of palliative care team physicians in a single facility may have led to prescribing preferences that were potentially biased. Therefore, conducting similar analyses across multiple facilities is necessary to improve generalizability.

CONCLUSION

This study is the first to report, using the DDD method, on opioid-prescribing trends of strong and weak opioids in Japan, and on these trends in patients with or without palliative care team support. The number of opioid prescriptions in Japan changed during the 7-year study period, indicating that the types of opioids used changed. Differing characteristics in opioid-prescribing trends were observed between patients who received palliative care team support and those who did not. Therefore, understanding annual trends in opioid use nationally and at institutions for pain management in patients with cancer is useful.

Funding

This work was supported by JSPS KAKENHI Grant Number: JP24K20169.

Author Contributions

T. Shoji, M. Akazawa, R. Inose, Y. Muraki, and T. Iijima conceived the study. T. Shoji and Y. Muraki analyzed the data. T. Shoji, M. Akazawa, N. Nakagomi, R. Inose, Y. Muraki, and T. Iijima interpreted the results. T. Shoji drafted the manuscript. M. Kobayashi, F. Kitta, and T. Suzuki reviewed and edited the manuscript. All authors have read the submitted manuscript and given their final approval for its publication.

Conflict of Interest

M. Akazawa has received consulting fees from Astellas Pharma Inc., GlaxoSmithKline K.K., Janssen Pharmaceutical K.K., MSD K.K., and Mitsubishi Tanabe Pharma Corporation. Y. Muraki has received funding for commissioned research from Kowa Company, Ltd. and for a medical education grant from Pfizer Japan, but this study is not directly related to that funding. The other authors declare no conflict of interest.

Data Availability

The NDB Open Data used in this study are publicly available and can be obtained from the following URL: https://www.mhlw.go.jp/stf/seisakunitsuite/bunya/0000177182.html. The DPC data used in this study are not publicly available as the participants of this study did not agree for their data to be shared publicly.

Supplementary Materials

This article contains supplementary materials.

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