Literature DB >> 33781215

Risk factors leading to trabeculectomy surgery of glaucoma patient using Japanese nationwide administrative claims data: a retrospective non-interventional cohort study.

Chikako Shirai1, Satoru Tsuda1, Kunio Tarasawa2, Kiyohide Fushimi3, Kenji Fujimori4, Toru Nakazawa5.   

Abstract

BACKGROUND: Early recognition and management of baseline risk factors may play an important role in reducing glaucoma surgery burdens. However, no studies have investigated them using real-world data in Japan or other countries. This study aimed to clarify the risk factors leading to trabeculectomy surgery, which is the most common procedure of glaucoma surgery, of glaucoma patient using the Japanese nationwide administrative claims data associated with the diagnosis procedure combination (DPC) system.
METHODS: It was a retrospective, non-interventional cohort study. Data were collected from patients who were admitted to DPC participating hospitals, nationwide acute care hospitals and were diagnosed with glaucoma between 2012 to 2018. The primary outcome was the risk factors associated with trabeculectomy surgery. The association between baseline characteristics and trabeculectomy surgery was identified using multivariable logistic regression analysis by comparing patients with and without trabeculectomy surgery. Meanwhile, the secondary outcomes included the rate of comorbidities, the rate of concomitant drug use and the treatment patterns of glaucoma eye drops at the index admission. Among patients with trabeculectomy surgery, the risk factors leading to cataract surgery were also evaluated as subgroup analysis.
RESULTS: A total of 29,599 patients included in the analysis, 12,038 and 17,561 patients were in the glaucoma surgery and non-glaucoma surgery cohorts, respectively. The factors associated with the increase in trabeculectomy surgery were having allergies, taking concomitant drugs including cancer, depression, ischemic heart disease and peptic ulcer, being diagnosed with primary open-angle glaucoma and longer length of stay in hospital. In contrast, the factors associated with the decrease in trabeculectomy surgery were having hypertension, taking hypertension drug, age ≥ 80 and female.
CONCLUSIONS: Special focus on Japanese patients with glaucoma who have allergy-related comorbidities or take immune, nervous, circulatory or gastrointestinal system-related concomitant drugs seems to be desirable.

Entities:  

Keywords:  Administrative claims data; Comorbidity; Concomitant; Diagnosis procedure combination (DPC); Glaucoma

Mesh:

Year:  2021        PMID: 33781215      PMCID: PMC8008563          DOI: 10.1186/s12886-021-01897-4

Source DB:  PubMed          Journal:  BMC Ophthalmol        ISSN: 1471-2415            Impact factor:   2.209


Background

Glaucoma is a chronic progressive optic neuropathy that can lead to irreversible blindness, affecting over 70 million adults worldwide. Intraocular pressure (IOP)-lowering therapy is the only effective strategy recognized to date [1-5]. In Japan, glaucoma is the most common cause of blindness, accounting for 28.6% of all blind regression [6]. It has an estimated prevalence of 5% in those aged over 40 years, that is, four million glaucoma patients [7]. Owing to the aging Japanese population, and glaucoma increases with age [8, 9], the future clinical and economic burden to the healthcare system is expected to increase. Current therapies used to lower IOP are drug treatment (usually eye drops), laser treatment, surgical treatment, or a combination of these treatments are used [5]. Surgical treatment is considered the final step in lowering IOP due to the improvement of drug treatment, and thus, patients with glaucoma undergoing surgical treatment represent severe or drug treatment resistance. Nevertheless, glaucoma surgery has incrementally advanced over the years. The search for safer and less invasive surgeries has been continued with emphasis on newer devices and techniques that use small incisions, a category described as micro-invasive glaucoma surgery [10-12]. New procedures for surgical treatment, however, have their own risks and complications, some of which might be unknown until long-term data become available. Besides, to the best of our knowledge, there have been no published study results analyzing what background of patients with glaucoma who are receiving surgical treatment in routine clinical practice. Therefore, such study, in particular an analysis of the glaucoma treatment using a large-scale administrative database, resulted in an important and useful information that reflects the current status of treatment and identifies issues to be considered. The aim of this study was to clarify the risk factors leading to trabeculectomy surgery of glaucoma patients using the Japanese nationwide administrative claims data associated with the diagnosis procedure combination (DPC) system [13, 14]. In addition, the rate of comorbidities, the rate of concomitant drug use, and the treatment patterns of glaucoma eye drops at the index admission in patients with and without trabeculectomy surgery were also explored.

Methods

Study design

This was a retrospective non-interventional cohort study using 6-year data (between 1 April 2012 and 31 March 2018) from the Japanese nationwide administrative claims data associated with the DPC system to identify the risk factors leading to trabeculectomy surgery of patients with glaucoma in Japan. Moreover, because glaucoma and cataract are leading causes of blindness worldwide and their co-existence is common in elderly people, the subgroup analysis was performed in patients with combined trabeculectomy and cataract surgery. This study was registered with UMIN Clinical Trials (UMIN000037878). It was approved by the research ethics committee of the Tohoku University Graduate School of Medicine, Japan (No. 2019–1-897) and conducted in accordance with The Code of Ethics of the World Medical Association (Declaration of Helsinki) for experiments involving human. Because this study was based on secondary analysis of DPC data that had already been anonymized unlinkable, written informed consent from patients was not required.

Data source and study cohort

The DPC is a national administrative database of a case-mix classification system for acute inpatient care developed in Japan. Details of the system have been described elsewhere [15, 16]. The system was launched in 2003 among 82 special functional hospitals, with a rapidly increasing number of hospitals having adopted the system, which recently includes approximately 7 million inpatients per year from more than 1000 hospitals, covering approximately 90% of all hospitalization to acute care hospital in Japan. The DPC data include administrative claims data and some clinical data. The DPC database includes data on the following elements: patient demographics (e.g., age and gender); primary diagnosis; comorbidities at admission; complications after admission; procedures including surgery, medication and devices used during hospitalization; length of stay; discharge status; and medical expenses [17-19]. The primary diagnosis is limited to one. In order to optimize the accuracy of the recorded diagnoses, the responsible physicians are required to record the diagnosed disease name in the medical charts. A wide variety of centers, including academic, urban and rural hospitals, use the DPC system [20]. These data were coded in the 10th revision of the International Statistical Classification of Disease (ICD10) and also the original Japanese code determined by the Ministry of Health, Labor and Welfare of Japan. For this study, patients were extracted from the DPC data using SQL Server 2014 Management Studio (Microsoft Corporation). Eligible patients were those who were admitted to DPC participating hospitals, that is, nationwide acute care hospitals in Japan and diagnosed with glaucoma. Patients with glaucoma as the disease associated with the code of “highest medical costs” in the DPC database, it means that the most causative disease of hospitalization, were identified based on the following ICD10codes: H401 (normal tension glaucoma, primary open-angle glaucoma and open-angle glaucoma) and H409 (unspecified glaucoma) from 1 April 2012 to 31 March 2018 (study period). The less common types including angle closer glaucoma (H402), secondary glaucoma (H403-H407) and other glaucoma (H408) were excluded. Figure 1 shows the patient selection process. Trabeculectomy surgery was defined as the following claim code for medical procedure: 150335910 (trabeculectomy, TLE). The trabeculotomy (TLO), as well as MIGS and implants, is often additionally used during cataract surgery, and is unlikely to be an indicator of severe glaucoma, while TLE is a standard surgery for glaucoma in the world. More effective in lowering IOP than TLO and rarely used for an additional surgery. To obtain an appropriate outcome of this study, we selected only TLE among glaucoma surgery (GS). The patients with glaucoma who had ≥2 records of GS, readmission to the DPC hospitals, < 12 months post-index continuous enrollment, in-hospital death or missing data during the study period were excluded, and furthermore, this study used the strict inclusion criteria that excluded data for the first and last year during the study period. The patients with only 1 record of TLE from 1 April 2013 to 31 March 2017 was defined as the newly undergone TLE (patients with TLE [GS cohort]).
Fig. 1

Flowchart for data extraction

Flowchart for data extraction On the other hand, patients who had not undergone TLE and all other GS (patients without GS [non-GS cohort]) were defined as those who had no record of GS during the study period and who had no record of GS from 1 April 2013 to 31 March 2017. Furthermore, to maintain the independence of observation and to exclude readmission to the DPC hospital, only the data associated with the last admission (index admission) from 1 April 2013 to 31 March 2017 were used as the data of the patients without GS. Among the patients with TLE, those who have undergone cataract surgery (CS) were defined as patients with CS (CS cohort). CS was defined as the following claim code for medical procedure: 150253010, 190179210, 190195910 (all 3 codes related to lens reconstruction). On the other hand, persons who had not undergone CS were defined as patients without CS (non-CS cohort).

Variables

Variable used in this study included age, gender, body mass index (BMI), smoking index, season at admission, length of stay in hospital (LOS), Charlson comorbidity index (CCI) [21, 22], comorbidities at index admission (17 disease as the possible risk factors for glaucoma: [23-26] hypertension, hypotension, ischemic heart disease, heart failure, stroke, diabetes, hyperlipidemia, electrolyte disorders, thyroid dysfunction, systemic lupus erythematosus, dementia, depression, mental disorders, cancer, allergies, peptic ulcer and liver insufficiency/failure), concomitant drugs at index admission (systemic oral drugs for the 17 disease listed above) and glaucoma related measure including glaucoma types, topical glaucoma drugs at index admission (see Table 1 for medical and pharmacy codes). Comorbidities and concomitant drugs were identified based on the medical code and the pharmacy code, respectively. Concomitant drugs used in the day of surgery were excluded. Topical glaucoma treatments included prostaglandin analog (PG), β blocker (BB), carbonic anhydrase inhibitor (CAI), α2 agonist (AA), α1 blocker (AB), αβ blocker (ABB), sympathomimetics, rho-associated coiled kinase inhibitor (ROCKI), fixed-combinations and their generics. Patients were categorized into 6 age groups: ≤39, 40–49, 50–59, 60–69, 70–79, ≥80; two gender groups: male, female; four BMI groups: thin (< 18.5), normal (≥18.5 < 25), fat (≥25), not classified; four season groups: spring (April–June), summer (July–September), autumn (October–December), winter (January–March); 4 CCI groups: low (0), medium (1, 2), high (3, 4), very high (≥5) cases.
Table 1

Medical and pharmacy codes used for the study

Therapeutic categoryICD-10 codesDrug codesaDrug generic name
HypertensionI10213, 214, 217
HypotensionI95%216
Ischemic heart diseaseI20%-I25%212, 214, 217
Heart failureI50%211, 213, 214, 217
StrokeI63%333, 339
DiabetesE10%-E14%396
HyperlipidemiaE78%218
Electrolyte disordersE87%321, 322
Thyroid dysfunctionE02%, E03%243
Systemic lupus erythematosusM32%2,456,001, 3,999,005, 3,999,038Prednisolone, Azathioprine, Hydroxychloroquine
DepressionF251, F31%-F35%1179
DementiaF00%-F03%1,190,012, 1,190,018, 1,190,019Donepezil, Memantine, Galantamine,
Mental disordersF09, F23, F28, F29117
CancerC00%-C97%421, 422, 423, 424, 429
AllergiesD690, D721, H011, H101, H169, H200, H650, H651, H654, H659, J301-J304, L23%, L500, T781, T784441, 442, 443, 449
Peptic ulcerF54, K221, K25%, K26%, K27%, K28%, K51%, K626, K633, K828, K838232
Liver insufficiency/failureK70%-K77%625, 6399, 3919, 3999
Glaucoma (NTG/POAG/OAG)H401131b
Unspecified glaucomaH409131b

ICD-10 international classification of disease, NTG normal tension glaucoma, OAG open angle glaucoma, POAG primary open angle glaucoma

aClassified by the Drug Therapeutic Class Code in Japan

bFurthermore, commonly prescribed glaucoma eye drops were narrowed down by the Japanese National Health Insurance drug price listing pharmaceuticals code

Medical and pharmacy codes used for the study ICD-10 international classification of disease, NTG normal tension glaucoma, OAG open angle glaucoma, POAG primary open angle glaucoma aClassified by the Drug Therapeutic Class Code in Japan bFurthermore, commonly prescribed glaucoma eye drops were narrowed down by the Japanese National Health Insurance drug price listing pharmaceuticals code

Study outcomes

The primary outcome was the risk factors associated with TLE using patients’ baseline demographic and clinical characteristics at the index admission. The secondary outcomes were the rate of comorbidities, the rate of concomitant use of prescribed systemic oral drugs and the treatment patterns of prescribed topical glaucoma drugs (eye drops) at the index admission in the GS and non-GS cohorts. Furthermore, GS cohort was divided into two cohorts based on with or without CS. The primary and secondary outcomes were also performed.

Statistical analysis

Descriptive analysis was performed for the basic features of the data as in mean with standard deviation (SD) for continuous variables and frequency (n) and percentage (%) for categorical variables. For outcomes, the difference between the GS and non-GS cohorts were compared according to baseline characteristics. Based on variable types and normality, the Chi-square test (or Fisher’s exact test, if cell expectations were less than 5), the Student’s t-test and the Mann-Whitney U test were used to examine differences. To identify the factors associated with TLE, logistic regression analysis was used. Potentially significant variables on univariable analysis (p < 0.05) were considered a priori for inclusion in a multivariable logistic regression model. Pairwise correlation coefficients were examined between variables that were potentially related before inclusion in our multivariable model to avoid collinearity. Stepwise forward-backward elimination analysis was performed and variables with p < 0.0001 were retained in the final multivariable model. In order to validate the final model, the variance inflation factor (VIF) was performed to test for multicollinearity among the predictor variables. A VIF exceeding 10 was regarded as indicating serious multicollinearity, and values greater than 4.0 was considered a cause for concern [27-29]. P -values, adjusted odds ratios (ORs) and Wald 95% confidence intervals (CIs) were obtained for the predictor variables. Furthermore, stratified analysis by CS were also performed. All the statistical analyses were performed using the JMP Pro Ver 14.0 (SAS Institute Inc., Cary, NC, USA). P-values of < 0.05 were considered statistically significant.

Results

A total of 29,599 patients met all inclusion criteria for this study, of whom 12,038 (40.7%) patients were in the GS cohort and 17,561 (59.3%) patients were in the non-GS cohorts (Fig. 1). The non-GS cohort was considered to be patients who were hospitalized because of the sudden increase in IOP, however, cured and discharged only by drug treatment. Furthermore, it might have been hospitalized for a glaucoma medical checkup. Among the GS cohort, 2991 (24.8%) patients were in the CS cohort and 9047 (75.2%) patients were in the non-CS cohorts. The baseline demographics and clinical characteristics of the GS and non-GS cohorts are summarized in Table 2. The mean age was 68 years and 55.6% were male, and most patients had a moderate BMI and a low CCI. In unadjusted comparison, the GS cohort significantly had a higher percentage of patients with age 50–59 or 60–69 (P < 0.0001 each); male (P < 0.0001); normal BMI (P = 0.0313); longer LOS (P < 0.0001); 2 comorbidities at the index admission: diabetes (P = 0.0101) and allergies (P < 0.0001); 11 concomitant drugs at index admission: ischemic heart disease, stroke, diabetes, systemic lupus erythematosus, depression, mental disorders, cancer, allergies, peptic ulcer (P < 0.0001 each), hyperlipidemia (P = 0,0016) and liver insufficiency/failure (P = 0.0294); and a diagnosis of primary open angle glaucoma (POAG) (P < 0.0001) than the non-GS cohort, whereas significantly had a lower percentage of patients with age ≤ 39 or ≥ 80 (P < 0.0001 each); female (P < 0.0001); autumn season admission (P = 0.0041); 1 comorbidity at index admission: hypertension (P = 0.0009): 2 concomitant drugs at index admission: hypertension and heart failure (P < 0.0001 each); and a diagnosis of normal tension glaucoma (NTG) (P < 0.0001). Concerning the season of hospital admission, we thought that IOP rises in winter and trabeculectomy would be more frequent, however, medical big data such as the Japanese nationwide database which has more than forty million acute care hospitalized patients registered, did not show seasonal difference.
Table 2

Baseline demographic and clinical characteristics of the study cohorts

VariableGlaucoma surgery(N = 12,038)Non-glaucoma surgery(N = 17,561)
nPercentage ormean ± SDnPercentage ormean ± SDP Value
Age (years)12,03868.5 ± 12.417,56168.8 ± 14.0< 0.0001*
 Category< 0.0001
  ≤ 393052.57194.1< 0.0001
  40–496285.29295.30.7910
  50–59148812.4184210.5< 0.0001
  60–69322726.8416823.7< 0.0001
  70–79420734.9606964.60.4943
  ≥ 80218318.1303421.8< 0.0001
Gender
 Category< 0.0001
  Male703258.4937653.4< 0.0001
  Female500641.6818546.6< 0.0001
Body mass index (kg/m2)12,03822.7 ± 4.317,56122.2 ± 6.2< 0.0001*
 Category< 0.0001
  Thin (< 18.5)10768.915658.90.9504
  Normal (≥18.5 < 25)786765.411,26264.10.0313
  Fat (≥25)296924.7422024.00.2144
  Not classified1261.05142.9< 0.0001
Smoking index12,03891.3 ± 288.517,56189.9 ± 290.6 14.00.9622*
 Maximum00
 Minimum50004995
Season
 Category0.0303
  Spring (April–June)329527.4465926.50.1093
  Summer (July–September)250420.8364420.80.9187
  Autumn (October–December)252020.9392222.30.0041
  Winter (January–March)371930.9533630.40.3553
Length of stay in hospital12,03812.1 ± 6.117,5618.6 ± 6.0< 0.0001*
 Maximum11
 Minimum99128
Charlson comorbidity index
 Category0.4710
  Low (0)974881.014,28781.40.4135
  Medium (1, 2)217718.1310017.70.3457
  High (3, 4)1090.91620.90.9013
  Very High (≥5)40.0120.10.3085
Comorbidities
 Circulatory system
  Hypertension8527.114288.10.0009
  Hypotension20.050.00.7820
  Ischemic heart disease2922.44122.30.6694
  Heart failure820.71470.80.1377
  Stroke800.71180.71.0000
 Metabolic system
  Diabetes176314.6238613.60.0101
  Hyperlipidemia3853.25753.30.7166
  Electrolyte disorders1341.12321.30.1204
  Thyroid dysfunction140.1280.20.3512
  Systemic lupus erythematosus100.1280.20.0971
 Nervous system
  Dementia180.2430.20.0894
  Depression560.5880.50.7339
  Mental disorders10.000.00.4067
 Immune system
  Cancer1100.91550.90.8017
  Allergies9818.15423.1< 0.0001
 Gastrointestinal system
  Peptic ulcer1811.52211.30.0821
  Liver insufficiency/failure300.2350.20.3784
Concomitant drug
 Circulatory system
  Hypertension341628.4554631.6< 0.0001
  Hypotension360.3560.30.8319
  Ischemic heart disease212517.7262514.9< 0.0001
  Heart failure365630.4573532.7< 0.0001
  Stroke294224.4305317.4< 0.0001
 Metabolic system
  Diabetes5884.96353.6< 0.0001
  Hyperlipidemia7776.59775.60.0016
  Electrolyte disorders123310.2190710.90.0909
  Thyroid dysfunction780.61060.60.6518
  Systemic lupus erythematosus3032.53011.7< 0.0001
 Nervous system
  Dementia450.4840.50.2084
  Depression251820.9200511.4< 0.0001
  Mental disorders252221.0201211.5< 0.0001
 Immune system
  Cancer931377.4399722.8< 0.0001
  Allergies4363.64332.5< 0.0001
 Gastrointestinal system
  Peptic ulcer33618.5245014.9< 0.0001
  Liver insufficiency/failure22302.84182.40.0294
Glaucoma types
 POAG440436.6562832.0< 0.0001
 OAG421435.0630036.00.1253
 NTG7436.213317.6< 0.0001
 Not classified267722.2432024.5< 0.0001
Glaucoma drug by class
 PG282723.5392322.30.0215
 BB7135.912126.90.0008
 CAI10869.014458.20.0168
 ROCKI6945.89285.30.0771
 AA164013.3231713.20.7534
 AB1311.11410.80.0130
 ABB140.1170.10.7151
 Sympathomimetics120.1110.10.2655
 PG/BB fixed combination2962.54252.40.8479
 CAI/BB fixed combination7135.912126.90.0008
Glaucoma drug by generic name
 PG
  Isopropyl Unoprostone40.0130.10.2165
  Isopropyl Unoprostone GE00.000.0NA
  Latanoprost9177.612727.20.2309
  Latanoprost GE1521.32381.40.5050
  Travoprost3773.15503.11.0000
  Travoprost GE00.000.0NA
  Tafluprost3673.06693.80.0004
  Tafluprost GE00.000.0NA
  Bimatoprost10698.912747.3< 0.0001
  Bimatoprost GE00.000.0NA
 BB
  Timolol Maleate4353.67614.30.0020
  Timolol Maleate GE520.4730.40,8544
  Carteolol Hydrochloride2171.83672.10.0813
  Carteolol Hydrochloride GE100.1120.10.6687
  Betaxolol Hydrochloride20.050.00.7082
  Betaxolol Hydrochloride GE00.010.01.0000
 CAI
  Dorzolamide Hydrochloride2251.92951.70.2243
  Dorzolamide Hydrochloride GE00.000.0NA
  Brinzolamide6865.79145.20.0670
  Brinzolamide GE00.000.0NA
 ROCKI
  Ripasudil Hydrochloride Hydrate6945.89285.30.0771
  Ripasudil Hydrochloride Hydrate GE00.000.0NA
 AA
  Brimonidine Tartrate160413.3231713.20.7534
  Brimonidine Tartrate GE00.000.0NA
 AB
  Bunazosin Hydrochloride1311.11410.80.0130
  Bunazosin Hydrochloride GE00.000.0NA
 ABB
  Levobunolol Hydrochloride20.010.00.5705
  Levobunolol Hydrochloride GE00.000.0NA
  Nipradilol130.1160.10.7067
  Nipradilol GE00.010.01.0000
 Sympathomimetics
  Dipivefrin Hydrochloride120.1110.10.2917
  Dipivefrin Hydrochloride GE00.000.0NA
 PG/BB fixed combination
  Lat/Tim1140.92111.20.0409
  Lat/Tim GE00.000.0NA
  Lat/Car10.030.00.6560
  Lat/Car GE00.000.0NA
  Tra/Tim1411.21630.90.0459
  Tra/Tim GE00.000.0NA
  Taf/Tim410.3510.30.4582
  Taf/Tim GE00.000.0NA
 CAI/BB fixed combination
  Dor/Tim151912.6232713.30.1133
  Dor/Tim GE00.000.0NA
  Brinzolamide/Tim3593.05473.10.5364
  Brinzolamide/Tim GE00.000.0NA

AA α2-agonist, AB α1-blocker, ABB αβ-blocker, BB β-blocker, CAI carbonic anhydrase inhibitor, Dor dorzolamide hydrochloride, GE generic, Lat latanoprost, NA not assessed, NTG normal tension glaucoma, OAG open angle glaucoma, PG prostaglandin analog, POAG primary open angle glaucoma, ROCKI rho-associated protein kinase inhibitor, SD standard deviation, Taf tafluprost, Tim timolol maleate, Tra travoprost

*Calculated using the Mann-Whitney U test; the remaining P Values were calculated with the Chi-square test or Fisher’s exact test

Baseline demographic and clinical characteristics of the study cohorts AA α2-agonist, AB α1-blocker, ABB αβ-blocker, BB β-blocker, CAI carbonic anhydrase inhibitor, Dor dorzolamide hydrochloride, GE generic, Lat latanoprost, NA not assessed, NTG normal tension glaucoma, OAG open angle glaucoma, PG prostaglandin analog, POAG primary open angle glaucoma, ROCKI rho-associated protein kinase inhibitor, SD standard deviation, Taf tafluprost, Tim timolol maleate, Tra travoprost *Calculated using the Mann-Whitney U test; the remaining P Values were calculated with the Chi-square test or Fisher’s exact test Regarding the primary outcome on the risk factors associated with TLE, the 28 variables previously mentioned were included in the initial regression model. Stepwise logistic regression with forward-backward elimination retained 11 of the 20 variables as the significant predictors (P < 0.0001). The VIFs for the predictor variables in this study were all < 4.0, indicating the absence of multicollinearity. Table 3 lists the variables estimated for the final model. The use of cancer drug (adjusted OR: 0.0862, 95% CI: 0.0816–0.0911) and having allergies including systemic and topical (adjusted OR: 0.3590, 95% CI: 0.3223–0.3997) were the most significant predictors of TLE, followed by using concomitant drugs including depression, ischemic heart disease and peptic ulcer; being diagnosed with POAG; and longer LOS. In contrast, the use of hypertension drug (adjusted OR: 1.1651, 95% CI: 1.1073–1.2258) and having hypertension (adjusted OR: 1.1621, 95% CI: 1.0640–1.2693) was most strongly associated with reduced likelihood of TLE followed by age ≥ 80 and female. When we restricted the multivariable analysis to the subgroup of patients with TLE who had undergone CS, the association between increase CS and baseline characteristics (P < 0.0001); age 70–79 and being diagnosed with POAG were also significant in the model (Table 4).
Table 3

Logistic regression analysis of factors associated with or without trabeculectomy surgery

VariableEstimateAdjusted OR (95% CI)P Value
Hypertension drug0.6491551.1651(1.1073–1.2258)< 0.0001
Hypertension0.333621.1621(1.0640–1.2693)< 0.0001
Age ≥ 800.1745071.2609(1.0189–1.3370)< 0.0001
Female0.1514421.2263(1.1702–1.2851)< 0.0001
Length of stay in hospital−0.069790.8942 (0.8899–0.8984)< 0.0001
POAG−0.172280.8175(0.7789–0.8584)< 0.0001
Peptic ulcer drug−0.273030.7131(0.6697–0.7593)< 0.0001
Ischemic heart disease drug−0.299490.8199(0.7701–0.8728)< 0.0001
Depression drug−0.41210.4873(0.4571–0.5195)< 0.0001
Allergies−0.578120.3590(0.3223–0.3997)< 0.0001
Cancer drug−2.236320.0862(0.0816–0.0911)< 0.0001

CI confidence interval, OR odd ratio, POAG primary open angle glaucoma

Table 4

Logistic regression analysis of factors associated with or without combined trabeculectomy and cataract surgery

VariableEstimateAdjusted OR (95% CI)P Value
Age ≤ 392.625231.2066(6.2634–25.5751)< 0.0001
Age 40–491.60363347,396(3.4675–6.4783)< 0.0001
Age 50–590.9652752.6394(2.2454–3.1026)< 0.0001
Cancer drug0.3846521.4361(1.3062–1.5789)< 0.0001
Hyperlipidemia drug0.1947871.2737(1.0657–1.5222)< 0.0001
POAG−0.173530.8450(0.7761–0.9199)< 0.0001
Age 70–79−0.285790.5642(0.5184–0.6140)< 0.0001

CI confidence interval, OR odd ratio, POAG primary open angle glaucoma

Logistic regression analysis of factors associated with or without trabeculectomy surgery CI confidence interval, OR odd ratio, POAG primary open angle glaucoma Logistic regression analysis of factors associated with or without combined trabeculectomy and cataract surgery CI confidence interval, OR odd ratio, POAG primary open angle glaucoma The rate of comorbidities and the rate of concomitant use of prescribed systemic oral drugs in the GS and non-GS cohorts are shown in Fig. 2. The most common comorbidity was diabetes in both, the GS (14.6%) and non-GS cohort (13.6%). Diabetes was followed by allergy, hypertension, hyperlipidemia and Ischemic heart disease. Allergy was remarkably higher in the GS cohort (Fig. 2a). Concomitant drugs use with frequency > 10% and significant difference in the two cohorts were hypertension, Ischemic heart disease, heart failure, stroke, depression, mental disorders, cancer and peptic ulcer. The use of cancer drug was remarkably higher in the GS cohort. (Fig. 2b). On the other hand, mitomycin C (MMC) originally was used as a systemic chemotherapeutic agent, and it has been used widely in ophthalmic practice, during and after surgery, for enhancing the success rate of glaucoma filtration surgery. Since concomitant drugs were limited to oral drugs and were excluded drugs used in the day of surgery, this study did not include MMC in the cancer drugs.
Fig. 2

a Prevalence rate of comorbidities, b rate of concomitant use of prescribed systemic oral drugs in the glaucoma surgery and non-glaucoma surgery cohorts

a Prevalence rate of comorbidities, b rate of concomitant use of prescribed systemic oral drugs in the glaucoma surgery and non-glaucoma surgery cohorts Among the GS cohort, the rate of comorbidities and the rate of concomitant use of prescribed systemic oral drugs in the CS and non-CS cohorts are shown in Fig. 3. The most common comorbidity was diabetes in both, the CS (17.7%) and non-CS cohort (19.3%). Diabetes was followed by allergy and hypertension; however, the lack of significant differences was shown between the two cohorts (Fig. 3a). Concomitant drugs use with frequency > 10% and significant difference in the two cohorts were depression, mental disorders, and cancer (Fig. 3b).
Fig. 3

a Prevalence rate of comorbidities, b rate of concomitant use of prescribed systemic oral drugs in the cataract surgery and non-cataract surgery combined with glaucoma surgery cohorts

a Prevalence rate of comorbidities, b rate of concomitant use of prescribed systemic oral drugs in the cataract surgery and non-cataract surgery combined with glaucoma surgery cohorts The treatment patterns of prescribed topical glaucoma drugs (eye drops) at the index admission are summarized in Figs. 4 and 5. In the GS cohort, PG accounted for one third of total glaucoma eye drops. PG [2827 (23.5%)] was followed by AA [1640 (13.3%)], CAI [1086 (9.0%)] and BB [713 (5.9%)] by drug class; the most commonly used as first-line treatment was bimatoprost (8.9%) followed by latanoprost (7.6%), travoprost (3.1%) and tafluprost (3.0%) by generic name, including only original drugs not generic drugs (Fig. 4a). In the non-GS cohort, which has the similar treatment pattern to the GS cohort, PG [3923 (22.3%)], AA [2317 (13.2%)], CAI [1445 (8.2%)] and BB [1212 (6.9%)] were used by drug class, and the most commonly used as first-line treatment was bimatoprost (7.3%), followed by latanoprost (7.2%), tafluprost (3.8%) and travoprost (3.1%) by generic name (Fig. 4b). In the CS cohort, PG accounted for one third of total glaucoma eye drops. PG [673 (29.2%)] was followed by AA [372 (16.2%)], CAI [301 (13.1%)] and BB [203 (8.8%)] by drug class; the most commonly used as first-line treatment was latanoprost (10.2%), followed by bimatoprost (9.3%), travoprost (4.4%) and tafluprost (4.1%) by generic name (Fig. 5a). In the non-CS cohort, which has the similar treatment pattern to the CS cohort, PG [2154 (30.7%)], AA [1232 (17.6%)], CAI [785 (11.2%)] and ROCK [557 (7.9%)] were used by drug class, and the most commonly used as first-line treatment was bimatoprost (12.2%), followed by latanoprost (9.7%), travoprost (3.9%) and tafluprost (3.9%) by generic name (Fig. 5b).
Fig. 4

Treatment patterns of prescribed topical glaucoma drugs (eye drops) at the index admission in the glaucoma surgery (a) and non-glaucoma surgery (b) cohorts. AA, α2-agonist; AB. α1-blocker; ABB, αβ-blocker; BB, β-blocker; Bim, bimatoprost; CAI, carbonic anhydrase inhibitor; Lat, latanoprost; PG, prostaglandin analog; ROCKI, Rho-associated protein kinase inhibitor; Sym, sympathomimetics; Taf, tafluprost; Tra, travoprost

Fig. 5

Treatment patterns of prescribed topical glaucoma drugs (eye drops) at the index admission in the cataract surgery (a) and non-cataract surgery (b) combined with glaucoma surgery cohorts. AA, α2-agonist; AB. α1-blocker; ABB, αβ-blocker; BB, β-blocker; Bim, bimatoprost; CAI, carbonic anhydrase inhibitor; Lat, latanoprost; PG, prostaglandin analog; ROCKI, Rho-associated protein kinase inhibitor; Sym, sympathomimetics; Taf, tafluprost; Tra, travoprost

Treatment patterns of prescribed topical glaucoma drugs (eye drops) at the index admission in the glaucoma surgery (a) and non-glaucoma surgery (b) cohorts. AA, α2-agonist; AB. α1-blocker; ABB, αβ-blocker; BB, β-blocker; Bim, bimatoprost; CAI, carbonic anhydrase inhibitor; Lat, latanoprost; PG, prostaglandin analog; ROCKI, Rho-associated protein kinase inhibitor; Sym, sympathomimetics; Taf, tafluprost; Tra, travoprost Treatment patterns of prescribed topical glaucoma drugs (eye drops) at the index admission in the cataract surgery (a) and non-cataract surgery (b) combined with glaucoma surgery cohorts. AA, α2-agonist; AB. α1-blocker; ABB, αβ-blocker; BB, β-blocker; Bim, bimatoprost; CAI, carbonic anhydrase inhibitor; Lat, latanoprost; PG, prostaglandin analog; ROCKI, Rho-associated protein kinase inhibitor; Sym, sympathomimetics; Taf, tafluprost; Tra, travoprost

Discussion

To date, we found no other studies that identified the risk factors associates with TLE in patients with glaucoma in Japan or other countries. Our study did and revealed a significant influence of 11variables on TLE extracted from the claims database. Of these, 7 were significant more likely to increase TLS, and 4 were significant more likely to decrease TLE. The immune-related comorbidities and concomitant drugs use were the most likely to be TLE. Although there was no difference in the treatment pattern of prescribed glaucoma eye drops between the GS cohort and the non-GS cohort, the rate of the comorbidities and the rate of concomitant drugs use were similar trend to the above identified variables. Therefore, careful management of glaucoma patients with these variables may be important factor for reducing glaucoma surgery burden. In Japan, TLO is also often preferred as glaucoma surgery, and TLE may target relatively severe glaucoma patients. Since this study used DPC data collected form patients who were admitted to the nationwide acute care hospitals, we assumed that patients with relatively severe glaucoma were included and considered appropriate to select only TLE among GS. On the other hand, since TLO such as microhook TLO is often additionally used during CS, it is difficult to be an indicator for estimating exacerbation risk of glaucoma. Among the 17 disease as the possible risk factors for glaucoma [23-26] (see in the Method section), allergies were identified as the risk factors of comorbidities leading to TLE. Our finding might be explained by the previous studies: the toll-like receptor 4 (TLR4), a transmembrane receptor that mediates immune responses to exogenous, is associated with the risk of NTG [30]. The microglia are related to the immunocompetent cells of the central nervous system, and microglial activation has been reported in glaucoma [31], which might contribute to a higher prevalence of immune-related comorbidities such as allergies. Use of steroids by any route, however, can lead to increased IOP and can cause optic neuropathy resulting in steroid-induced glaucoma [32, 33]. Although our study included oral prednisolone use during the admissions (approximately 2.0%), a history of corticosteroids use was excluded. Also, steroid-induced glaucoma (ICD-10: H406) was excluded so that corticosteroids as a potential confounding factor would be less influence between allergies and glaucoma. Among systemic oral drugs for the 17 disease, cancer, depression, ischemic heart disease or peptic ulcer were identified as the risk factors of concomitant drugs leading to GS. According to the previous studies, the downregulation of cell cycle progression by checkpoint inhibitors has recently been targeting for cancer therapy [34, 35], can cause cell death beyond cancer cells, and therefore may induce neurodegenerative disorders such as glaucoma [36]. However, one of the risk factors for glaucoma is increased oxidative stress, and drugs targeting oxidative stress in cancer could reduce the oxidative stress-induced apoptosis of retinal ganglion cells in glaucoma [37, 38]. Therefore, we have not been able to identify reports from previous studies of whether cancer drugs is associated with TLE. According to Table 2, only 110 patients in the GS cohort (0.9%) and 155 patients in the non-GS cohort (0.9%) had cancer. However, 9313 patients in the GS cohort (77.4%) and 3997 patients in the non-GS cohort (22.8%) used medications for cancer. From these, the GS cohort used more medication for cancer than the non-GS cohort and would be considered more sever stage of glaucoma. Since pharmacy codes that used medications for cancer include 421 (alkylating agents), 422 (antimetabolites), 423 (antibiotics), and 424 (plant extract preparations), cancer treatments may have been used not only for cancer patients but also non-cancer patients. Other studies report that depression is strongly linked with glaucoma [39] and results in elevated oxidative stress [40]. Likewise, ischemic heart disease is linked with glaucoma probably affect vasculature dysfunction [41]. Furthermore, many factors contribute to peptic ulcer including glaucoma [42] is another likely reason that may contribute to the positive association. In contrast, hypertension and its drug were identified as the risk factors leading to non-GS. Our finding might to be in line with the previous studies that hypertension improve ocular blood flow [43], however, hypertension oral administration is a risk of glaucoma progression [44]. Stratified analysis based in CS showed that none of the 17 disease were identified as the risk factors leading to CS combined with TLE. In addition, patients with POAG was also identified as the significant more likely to be TLE. The rate for glaucoma type in subjects 40 years of age and older was estimated at 5.0% for all glaucoma, 0.3% for POAG, and 3.6% for NTG [5]. In contrast, this study showed that the rates of POAG, OAG and NTG at the index admission were 36.6, 35.0 and 6.2%, respectively, in the GS cohort, and 32.0, 36.0 and 7.6%, respectively, in the non-GS cohort. The ratios of NTG seem to be fewer than expected. One possible explanation could be that the rate of progress of glaucomatous optic neuropathy among patients with NTG is generally slower than that among those with other types of glaucoma, therefore, patients with NTG have less need to go to DPC hospitals. Furthermore, this study identified longer LOS as the factors associate with TLE. Japanese hospitals generally provide rehabilitation and nursing care in addition to acute medical care, which may contribute to the longer LOS. Patients in both cohorts, the high rate of comorbidities and concomitant drugs use were similar trend to the above identified variables. In the GS cohort, allergy and cancer drugs were most significantly higher than the non-GS cohort. Diabetes was the most common comorbidities in both, the GS (14.6%) and non-GS cohort (13.6%), and significantly higher in the GS cohorts, but not identified as the risk factors leadings to GS. On the other hand, the rate of the diabetes drug use was low in both, the GS (4.9%) and non-GS cohort (3.6%). Since the diabetes drug has been reported as both a risk factor and a protective factor for glaucoma [23-26], this study show that few patients with glaucoma who had diabetes may be treated with the diabetes drug. The treatment patterns of prescribed glaucoma eye drops at the index admission was similar between the two cohorts; PG was most commonly prescribed, AA and CAI were second and third, respectively. Our result is in line with the data from a published report indicating that the most commonly used first-line monotherapy was a PG [45-48], while CAI/BB was the most commonly used fixed combination as first- and second-line treatment [49, 50]. Although BB is also recommended as a first-line monotherapy in the guideline for glaucoma, the prescription rate of BB was low in this study. This is probably because the patients had comorbidities of asthmas, chronic obstructive pulmonary disease or heart failure may not prescribed BB according to the respective drug information. Or elderly patients may have difficult using BB. On the other hand, BB was considered to be common in the GS cohorts because of bradycardia, but not so in our results. The ROCKI as well as the EP2 receptor agonist become available in Japan recently and has been reported to show an additional IOP-lowering in combination with other glaucoma ophthalmic solutions [51-54]. Thus, the prescription trend for glaucoma eye drops may change in the future. This study had several limitations. First, we included only DPC hospitals with glaucoma beds, so the results may not be generalizable; however, DPC database contains detailed medical data on numerous patients residing throughout the Japan in a broad array of geographic regions. Moreover, the variables included in the final predictive model are available in other Japanese administrative claims databases. Second, limitations common to studies using administrative claims data apply to this study [55-58]. These limitations include lack of certain information in the database and errors or omissions in claims coding. Third, claims data lack clinical information (such as IOP, visual field, etc.) to access disease severity. Therefore, it was not possible to evaluate whether the severity level of documented comorbid conditions was comparable between our study cohorts and whether different stages of glaucoma were associated with specific comorbidity profiles. Fourth, our data did not exclude laser trabeculoplasty (LT). Although, LT reported to be an alternative to topical glaucoma drug treatment and the same IOP-lowering effect as eye drops as monotherapy [59], it may have influenced the results of our analysis. Fifth, unmeasured confounders may limit the findings. Finally, the present analyses were built according to the assumption that all the claimed drugs were used by the patients. To address these limitations, we need to conduct further studies using the real-world data combined with clinical data.

Conclusions

The results of this study show that the risk factors leading to TLE of glaucoma patient can be predicted with 7 commonly available demographic and administrative claim-based variables including: having comorbidities related to allergies; taking concomitant drugs related to cancer, depression, ischemic heart disease and peptic ulcer; being diagnosed with POAG, and longer LOS. Furthermore, the rate of comorbidities and the rate of concomitant drug use were similar tendency as the above identified variables. Therefore, before starting glaucoma treatment, special focus on Japanese patients with glaucoma, especially POAG, who have allergy-related comorbidities, or take the immune, nervous, circulatory or gastrointestinal system-related concomitant drugs, through medical interview by ophthalmologists seems to be desirable. Additional file 1: Supplemental Table 1. Baseline demographic and clinical characteristics of the study subgroups.
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