Clinical outcomes of flomoxef versus cefmetazole in hospitalized patients with urinary tract infections: combined retrospective analyses of two real-world databases and in vitro data

Abstract

Background

Flomoxef and cefmetazole have been reported to be effective against broad-spectrum β-lactamase-producing bacteria and have gained attention as a potential alternative to carbapenems. This study aimed to compare the efficacy of these two drugs in treating urinary tract infection (UTI) by integrating in vitro data and two real-world databases.

Methods

The susceptibility rates of third-generation cephalosporin-resistant Escherichia coli and Klebsiella pneumoniae to flomoxef and cefmetazole were compared using comprehensive national antimicrobial resistance surveillance data. Combined antimicrobial activities against an extended-spectrum beta-lactamase (ESBL)-producing multidrug-resistant bacterial strain were tested by diagonal measurement of n-way drug interactions. The effectiveness of the two drugs in treating UTIs was compared using hospital stay duration data obtained from the Japan Medical Data Center (JMDC) Claims Database.

Results

Third-generation cephalosporin-resistant E. coli and K. pneumoniae, including ESBL-producing strains, were similarly susceptible to flomoxef and cefmetazole. In vitro assessment against an ESBL-producing multidrug-resistant strain revealed similar antimicrobial interaction patterns. JMDC Claims data analysis showed that the median hospital stay was 11 (95% confidence interval [CI]: 11–11) and 4 (95% CI: 3–5) days in the cefmetazole and flomoxef groups, respectively (log-rank test, P < 0.001). Moreover, the flomoxef group demonstrated a significantly lower frequency of adverse events such as C. difficile infection and renal failure.

Conclusions

The effectiveness of flomoxef is comparable to that of cefmetazole in treating UTIs without major complications. Thus, flomoxef is a viable treatment option for UTIs in locales with a high prevalence of ESBL-producing strains.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12916-025-04130-x.

Background

The increase in extended-spectrum beta-lactamase (ESBL)-producing bacteria has complicated the treatment of urinary tract infections (UTIs) and intra-abdominal infections due to resistance to various classes of antimicrobials [1–3]. Currently, carbapenems are the preferred treatment option for severe infections caused by ESBL-producing bacteria. However, carbapenem-resistant strains have emerged and spread, which has raised interest in treatment strategies that spare carbapenems [4].

Cefmetazole and flomoxef are antimicrobial agents that were originally developed in Japan. Cefmetazole is a cephamycin that has a broad spectrum of antibacterial activity against Enterobacterales, such as Escherichia coli and Klebsiella pneumoniae, as well as anaerobic bacteria, and is widely indicated for the treatment of UTI and intra-abdominal infections [5]. Flomoxef is an oxacephem that, like cefmetazole, is active against E. coli, K. pneumoniae, and other Enterobacterales and is indicated for the treatment of UTI and intra-abdominal infections [6, 7]. Flomoxef has been approved in Japan, China, Taiwan, and South Korea and has been used in clinical practice since 1988 [8]. Both cefmetazole and flomoxef have a methoxy group at the 7-position of cephalosporanic acid and are stable to hydrolysis by ESBL [9]. Cefmetazole and flomoxef demonstrate in vitro efficacy against ESBL-producing bacteria and are of increasing clinical importance as carbapenem-sparing therapeutic options for infections caused by ESBL-producing Enterobacterales [10, 11].

Although accumulated clinical data have reported comparable effectiveness of cefmetazole with carbapenems against infections due to ESBL-producing bacteria, clinical data regarding flomoxef remain limited [12, 13]. To the best of our knowledge, no national study has compared the susceptibility rates of flomoxef and cefmetazole among ESBL-producing Enterobacterales. Furthermore, no large study has compared the effectiveness of treatment with flomoxef and cefmetazole. In recent years, the resistance rate of cefmetazole in ESBL-producing E. coli has been shown to be higher than that of flomoxef [14, 15]. However, cefmetazole is more widely used in clinical practice, and given the recent instability in antimicrobial supply [16, 17], it would be beneficial to clarify the potential of flomoxef as a treatment option against ESBL-producing bacterial infections.

This study aimed to compare the usefulness of the two drugs by integrating in vitro data using a retrospective analysis of two real-world databases (National claims database and Nosocomial infections surveillance database).

Methods

Antimicrobial susceptibility profile of E. coli and K. pneumoniae clinical isolates based on the national antimicrobial resistance surveillance data

Data on bacterial isolates from inpatients in Japan between January 2014 and December 2021 were extracted from the national antimicrobial resistance surveillance program, the Japan Nosocomial Infections Surveillance (JANIS), which collects all routine microbiological diagnostic tests [18]. The JANIS datacenter recommends that MIC data be collected using the broth dilution method. In principle, antimicrobial susceptibility test results obtained using the disk method are excluded from tabulation. Additionally, if the same organism is detected more than once in the same patient, duplicate entries will be processed during tabulation [19]. A total of 2220 hospitals across Japan submitted their data to the JANIS database in 2021. We specifically targeted E. coli and K. pneumoniae due to their prevalence in UTIs. Data on antimicrobial susceptibility testing of isolates from urine and blood specimens were obtained, and the minimum inhibitory concentration (MIC) values of cefotaxime, cefmetazole, and flomoxef were analysed. We interpreted the MIC data for cefotaxime and cefmetazole using the 2023 Clinical and Laboratory Standards Institute (CLSI) criteria, which have remained unchanged since 2012. In this study, cefotaxime-resistant E. coli and K. pneumoniae isolates were considered as resistant to third-generation cephalosporins.

This part of the study was approved by the Ministry of Health, Labour, and Welfare (approval number: 1025–2) according to Article 32 of the Statistics Act.

in vitro drug interaction characterization

To focus on the individual efficacy of cefmetazole and flomoxef, we evaluated the potential synergistic or antagonistic effects when various antimicrobials were used in combination. Drug interactions were assessed using the diagonal measurement of n-way drug interactions (DiaMOND) method as previously described [20, 21]. An ESBL-producing, multidrug-resistant uropathogenic E. coli clinical strain UPEC GU2019-E4 [22] was used. Unless otherwise noted, bacterial cells were grown in a lysogeny broth medium at 37 °C under aerobic conditions. The bacterial cultures were diluted in fresh medium to an optical density at 600 nm (OD₆₀₀) of 0.001, and 50 μL of the diluted culture was added to each well of a clear flat-bottom 384-well microplate. Antimicrobial agents were dispensed using a digital dispenser (Multidrop pico8 digital dispenser; Thermo Fisher). After 22-h incubation at 37 °C without shaking, OD₆₀₀ was measured using a microplate reader (Bio Tek Synergy HTX plate reader: Agilent). The fractional inhibitory concentration index (FICI) was used to evaluate the combination effect of the drugs. Dose–response sampling for the combination was performed by measuring and calculating the 90% inhibition concentration (IC₉₀) values for each drug separately and creating a dilution series of the combined drugs at half the concentration of each drug’s IC₉₀ values. The growth inhibition assay was performed similarly to that for single drugs, and the OD₆₀₀ data obtained were used to calculate the IC₉₀, which was defined as the observed IC₉₀. The intersection of the line connecting the IC₉₀ values of each single drug and the diagonal line representing the dose response of the combination drug was defined as the expected IC₉₀.

Data source of the claims database analysis

Data from April 2014 to November 2021 in the Japan Medical Data Center (JMDC) Claims Database were used for the study. This database contains inpatient and outpatient claims, as well as the Diagnosis Procedure Combination (DPC) practice data from several health insurance associations. The DPC system is a comprehensive reimbursement system for acute inpatient care introduced in Japan in 2003 [23]. It is possible to extract diagnoses of injuries and diseases, drug prescriptions, weight, height, and activities of daily living (ADL) scores at the time of admission from the insurance claims and DPC practice data.

This part of the study was approved by the Ethics Committee of Tokushima University Hospital (protocol number: 4492). This study was conducted in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology Reporting Guidelines for Cohort Studies.

Study design of the claims database analysis

Patients with a confirmed diagnosis of UTI on the date of first admission following the initiation of record collection from each patient’s JMDC and who were prescribed cefmetazole or flomoxef on the same day were included. The diagnosis of UTI was based on the International Statistical Classification of Diseases and Related Health Problems 10 th Revision (ICD-10) Version 2016 of the World Health Organization (Additional File 1). The date of the first cefmetazole or flomoxef dose was set as the index date (Fig. 1). Certain patient groups were excluded: those not in the DPC wards, those without a UTI diagnosis on the antimicrobial prescription date, those who died within 24 h of admission, and those receiving both cefmetazole and flomoxef.

Fig. 1.

Analysis design of claim data analysis. Timeline for index date and associated time point. Abbreviations: JMDC, Japan Medical Data Center

Owing to the multiple outcomes and statistical methods used in this study, several analytic datasets were created: Dataset 1 comprised the dataset of all remaining patients after excluding those who met the exclusion criteria; Dataset 2 comprised only those patients who were discharged alive after excluding those who died during hospitalization; and Dataset 3 was created by 1:1 matching of patients administered cefmetazole and flomoxef by the propensity score for Dataset 2.

Definition of baseline characteristics and complications

Sex, age, body mass index (BMI), Barthel index, Japan coma scale (JCS), and various complications (sepsis, shock, and respiratory failure) were evaluated at the index date. BMI was classified as underweight (BMI < 18.5 kg/m²), normal weight (BMI 18.5–24.9 kg/m²), overweight (BMI 25.0–29.9 kg/m²), obese (BMI ≥ 30 kg/m²), and deficient, according to previous studies [24]. The Barthel Index consists of 10 items: feeding (0–10 points), bathing (0–5 points), grooming (0–5 points), dressing (0–10 points), bowel control (0–10 points), bladder control (0–10 points), voiding (0–10 points), chair movement (0–15 points), walking (0–15 points), and stair climbing (0–10 points). A higher score indicated a higher degree of independence in the ADLs. The JCS categorizes consciousness into four major grades based on reactive eye-opening. Grade 0 signifies awake consciousness. Grades 1–3, represented by a single digit, indicate awake status without any stimulus. Grades 10–30, denoted by two digits, describe a state where the individual awakens with stimulus but reverts to the previous state once the stimulus is removed. Finally, grades 100–300, expressed with three digits, correspond to a state where the individual does not arouse in response to any stimulus [25]. The JCS has been reported to correlate well with the globally used Glasgow coma scale [26]. The complications of sepsis, shock, and respiratory failure were evaluated based on the diagnoses listed in Additional File 2. The Charlson comorbidity index and history of diabetes were evaluated based on the diagnoses before the index date (Fig. 1). The Charlson comorbidity index was assigned to each patient according to a previous study [27]. History of diabetes or urinary tract abnormalities was defined based on the ICD-10 codes (Additional File 3).

Patient outcomes

The primary effectiveness outcome was the number of days from the index date to discharge. Secondary effectiveness outcomes were defined as 28-day mortality after the index date and carbapenem use within 7 days after the index date. Safety outcomes were defined as gastrointestinal adverse events (AEs) (non-C. difficile diarrhoea, C. difficile infection), renal-related AEs (kidney failure and other kidney dysfunctions), and hypersensitivity symptoms (anaphylactic shock and rash) (Additional File 4). Gastrointestinal- and renal-related AEs were analysed 1 month after the index date, and hypersensitivity symptoms were analysed 2 days after the index date. AEs were defined based on the ICD-10 codes and drug use (Additional File 4).

The primary effectiveness outcome was analysed using Datasets 2 and 3, and the secondary effectiveness outcomes were analysed using Dataset 1. Safety outcomes were analysed using Dataset 1.

Statistical analyses

Continuous variables are expressed as mean ± standard deviation, while categorical variables are reported as percentages. The standardized mean difference was used to identify differences in patient backgrounds between the cefmetazole and flomoxef groups.

Kaplan–Meier analysis was used to estimate the primary effectiveness outcome, namely the time from the initiation of cefmetazole or flomoxef treatment to discharge alive, and log-rank tests were used to evaluate differences. Cox regression analysis was performed using age, sex, Charlson comorbidity index, Brinkman index, BMI, JCS, comorbidities (diabetes, sepsis, shock, respiratory failure, acute prostatitis, acute tubule-interstitial nephritis, cystitis), underlying urinary tract abnormalities, Barthel index, mechanical ventilation and dialysis on the day of admission, and prescription of vasopressors (epinephrine, norepinephrine, dopamine, dobutamine, and vasopressin) on the index date as covariates that may affect prognosis. Hazard ratios (HRs) for survival and discharge were calculated. Propensity score matching with 1:1 matching was performed to balance baseline characteristics. Matching was performed using nearest neighbour matching with a caliper of 0.05. The propensity score was calculated using age, sex, Charlson comorbidity index, Brinkman index, BMI, JCS, comorbidities (diabetes, sepsis, shock, respiratory failure, acute prostatitis, acute tubule-interstitial nephritis, cystitis), underlying urinary tract abnormalities, Barthel index, mechanical ventilation and dialysis on the day of admission, and prescription of vasopressors (epinephrine, norepinephrine, dopamine, dobutamine, and vasopressin) on the index date. Kaplan–Meier analysis, log-rank test, and Cox regression analysis were performed on the crude and matched data. In the sensitivity analysis, we performed an inverse probability weighting (IPW) approach using the same covariates employed in the propensity score matching analysis to estimate stabilised weights through logistic regression model. The weights were applied to balance baseline characteristics across the comparison groups, and assess the treatment effects. This approach complemented our primary propensity score-matched analysis to evaluate the robustness of findings under different statistical assumptions.

For the secondary effectiveness outcome, logistic regression analysis was performed with age, sex, Charlson comorbidity index, Brinkman index, BMI, JCS, comorbidities (diabetes, sepsis, shock, respiratory failure, acute prostatitis, acute tubule-interstitial nephritis, cystitis), underlying urinary tract abnormalities, Barthel index, mechanical ventilation and dialysis on the day of admission, and prescription of vasopressors (epinephrine, norepinephrine, dopamine, dobutamine, and vasopressin) on the index date as covariates. The odds ratios (ORs) for 28-day mortality and prescriptions of carbapenems were calculated.

For safety outcomes, the frequencies were calculated and descriptively analysed for gastrointestinal, renal, hepatic, and hypersensitive AEs.

Statistical tests were two-tailed, with a p < 0.05 considered statistically significant, and performed using R version 4.2.1 (R Foundation for Statistical Computing, Vienna, Austria).

Role of funding

This work was supported by Japan Agency for Medical Research and Development (AMED) [grant number JP23wm0325037, JP24fk0108665, JP24fk0108683, JP24fk0108712, JP24fk0108642, JP24gm1610003, JP24wm0225029, JP24wm0225022, and JP23 gm1610013], JSPS KAKENHI Grant (23H02634, 23K27325), and Health Labour Sciences Research Grant, Ministry of Health, Labour and Welfare (25HA1004). The funders had no role in the study design; collection, analysis, and interpretation of data; writing of the report; or decision to submit for publication.

Results

Antimicrobial susceptibility of E. coli and K. pneumoniae isolated from urine and blood against cefmetazole and flomoxef

In total, 682,034 E. coli and 143,842 K. pneumoniae isolates from urine culture specimens, and 144,219 E. coli and 53,334 K. pneumoniae isolates from blood culture specimens underwent antimicrobial susceptibility testing for both cefmetazole and flomoxef (Table 1, Additional File 5). Among them, 1.4% of third-generation cephalosporin-resistant (3GC-R) E. coli isolates and 5.5% of 3GC-R K. pneumoniae isolates from urine had MICs of cefmetazole of ≥ 64 mg/L. On the other hand, 1.0% of 3GC-R E. coli isolates and 3.0% of 3GC-R K. pneumoniae isolates had MICs of flomoxef of ≥ 64 mg/L. Concerning blood culture specimens, 1.5% of 3GC-R E. coli isolates and 6.2% of 3GC-R K. pneumoniae isolates had MICs of cefmetazole of ≥ 64 mg/L. Meanwhile, 1.1% of 3GC-R E. coli isolates and 2.8% of 3GC-R K. pneumoniae isolates had MICs of flomoxef of ≥ 64 mg/L.

Table 1.

The MIC values for cefmetazole and flomoxef against E. coli and K. pneumoniae isolated from urine and blood samples

				Cefmetazole			Flomoxef
Specimen	Isolates	Total	≦16	32	≧64	≦16	32	≧64
Urine	E. coli (all)	682,034	674,654 (98.9)	4240 (0.6)	3140 (0.5)	675,602 (99.0)	4476 (0.7)	1956 (0.3)
	3rd Generation cephalosporin-resistant E. coli	164,276	159,774 (97.3)	2180 (1.3)	2322 (1.4)	160,129 (97.5)	2489 (1.5)	1658 (1.0)
	K. pneumoniae (all)	143,842	141,938 (98.7)	649 (0.5)	1255 (0.9)	142,537 (99.1)	744 (0.5)	561 (0.4)
	3rd Generation cephalosporin-resistant K. pneumoniae	14,937	13,843 (92.7)	272 (1.8)	822 (5.5)	14,051 (94.1)	439 (2.9)	447 (3.0)
Blood	E. coli (all)	144,219	142,719 (99.0)	872 (0.6)	628 (0.4)	142,964 (99.1)	853 (0.6)	402 (0.3)
	3rd Generation cephalosporin-resistant E. coli	31,455	30,516 (97.0)	468 (1.5)	471 (1.5)	30,606 (97.3)	493 (1.6)	356 (1.1)
	K. pneumoniae (all)	53,334	52,661 (98.7)	254 (0.5)	419 (0.8)	52,949 (99.3)	247 (0.5)	138 (0.2)
	3rd Generation cephalosporin-resistant K. pneumoniae	4053	3701 (91.3)	101 (2.5)	251 (6.2)	3797 (93.7)	141 (3.5)	115 (2.8)

Interaction of cefmetazole and flomoxef with other classes of antimicrobial agents

Next, we compared the antimicrobial drug interactions of cefmetazole and flomoxef against those of an ESBL-producing, multidrug-resistant E. coli strain. The checkerboard assay is the standard method to determine FICI as a measure of interaction between antimicrobial agents; however, the assay is labour-intensive and time-consuming. Thus, we employed the DiaMOND method, a recently developed high-throughput method to assess antimicrobial interactions in vitro (Fig. 2). As shown in Fig. 2a, we first determined the IC₅₀ and IC₉₀ values of cefmetazole, flomoxef, and 10 other antimicrobial drugs against E. coli GU2019-E4 (Fig. 2b). We then compared antimicrobial drug interactions of cefmetazole and flomoxef with ten different antimicrobial agents (Fig. 2c). We found that the two drugs showed similar antimicrobial drug interaction patterns, supporting our hypothesis that flomoxef is as active as cefmetazole, both by itself and in combination with other commonly used agents.

Fig. 2.

Antibacterial drug combination effects. a Experimental and analysis workflow for measuring drug combination effects using DiaMOND method. b IC₅₀ and IC₉₀ of the antibacterial drugs against E. coli GU2019-E4 strain. CMZ, cefmetazole; FMOX, flomoxef; AMK, amikacin; MIN, minocycline; TET, tetracycline; TGC, tigecycline; AZT, aztreonam; IPM, imipenem; MEM, meropenem; FOS, fosfomycin; CST, colistin; CIP, ciprofloxacin. GEN, gentamicin; STR, streptomycin; TOB, tobramycin. c Heatmap of the combination effects of 10 antimicrobial drugs on CMZ and FMOX. Drug interactions are assessed using log2(FIC₅₀) and log2(FIC₉₀) values: a log2(FIC) below 0 indicates synergy (represented in blue) and a log2(FIC) above 0 indicates antagonism (represented in red)

Baseline characteristics of the JMDC claims database

Between April 2014 and November 2021, 340,954 and 83,932 patients were prescribed cefmetazole and flomoxef in the JMDC database, respectively. The study comprised 4796 patients who received cefmetazole and 673 patients who received flomoxef (Fig. 3). This group formed Dataset 1. Dataset 2, which excluded patients who died in the hospital from Dataset 1, comprised 4552 and 658 patients treated with cefmetazole and flomoxef, respectively. In Datasets 1 and 2, before propensity score matching, significant differences were observed between the two groups regarding age, sex, BMI, Brinkman index, Barthel index, history of diabetes, complications (sepsis, shock, respiratory failure), and underlying urinary tract abnormalities (Table 2). Patients who received cefmetazole were more likely to be female, older, and have a history of diabetes mellitus and complications, such as sepsis, shock, and respiratory failure, compared to those who received flomoxef. Moreover, based on the JCS score, the state of consciousness was worse in the cefmetazole group than in the flomoxef group. In contrast, the flomoxef group had a higher proportion of patients with underlying urinary tract abnormalities than the cefmetazole group. After matching by propensity score, the two groups were similar with respect to baseline characteristics, except for an age.

Fig. 3.

Patient flowchart in the claim data analysis. Flow diagram of patient inclusion and set up of each dataset. Abbreviations: DPC, Diagnosis Procedure Combination

Table 2.

Characteristics of the patients at baseline

		Before matching								After matching
		Dataset 1				Dataset 2				Dataset 3
		Cefmetazole (n = 4796)	Flomoxef (n = 673)	P value	SMD	Cefmetazole (n = 4552)	Flomoxef (n = 658)	P value	SMD	Cefmetazole (n = 580)	Flomoxef (n = 580)	P value	SMD
Sex [% (N)]	Female	2999 (62.5)	240 (35.7)	< 0.01	0.56	2836 (62.3)	231 (35.1)	< 0.01	0.57	235 (40.5)	231 (39.8)	0.86	0.01
	Male	1797 (37.5)	433 (64.3)			1716 (37.7)	427 (64.9)			345 (59.5)	349 (60.2)
Age [mean (SD)]		78.8 (30.0)	69.4 (29.6)	< 0.01	0.32	78.0 (30.2)	68.9 (29.6)	< 0.01	0.3	73.4 (25.7)	68.5 (31.4)	< 0.01	0.17
BMI [% (N)]	Underweight	1110 (23.1)	134 (19.9)	< 0.01	0.27	1023 (22.5)	130 (19.8)	< 0.01	0.27	101 (17.4)	128 (22.1)	0.16	0.15
	Normal	2311 (48.2)	365 (54.2)			2219 (48.7)	359 (54.6)			319 (55.0)	301 (51.9)
	Overweight	607 (12.7)	113 (16.8)			598 (13.1)	112 (17.0)			111 (19.1)	96 (16.6)
	Obese	191 (4.0)	24 (3.6)			186 (4.1)	24 (3.6)			14 (2.4)	22 (3.8)
	NA	577 (12.0)	37 (5.5)			526 (11.6)	33 (5.0)			35 (6.0)	33 (5.7)
Brinkman index [% (N)]	0	3528 (73.6)	419 (62.3)	< 0.01	0.51	3339 (73.4)	407 (61.9)	< 0.01	0.51	355 (61.2)	389 (67.1)	0.18	0.15
	0–400	247 (5.2)	76 (11.3)			239 (5.3)	76 (11.6)			72 (12.4)	65 (11.2)
	400–800	219 (4.6)	72 (10.7)			214 (4.7)	71 (10.8)			56 (9.7)	52 (9.0)
	800–1200	114 (2.4)	59 (8.8)			111 (2.4)	59 (9.0)			46 (7.9)	29 (5.0)
	> 1200	671 (14.0)	47 (7.0)			633 (13.9)	45 (6.8)			51 (8.8)	45 (7.8)
	NA	17 (0.4)	0 (0.0)			16 (0.4)	0 (0.0)			0 (0.0)	0 (0.0)
Charlson comorbidity index [mean (SD)]		2.2 (2.5)	1.7 (2.1)	< 0.01	0.20	2.1 (2.4)	1.7 (2.1)	< 0.01	0.17	1.8 (2.3)	1.8 (2.2)	0.77	0.02
Barthel index [mean (SD)]		39.1 (42.6)	63.8 (44.4)	< 0.01	0.57	40.6 (42.8)	65.0 (44.1)	< 0.01	0.56	60.3 (43.1)	60.5 (45.0)	0.93	< 0.01
Diabetes [% (N)]		1257 (26.2)	107 (15.9)	< 0.01	0.25	1177 (25.9)	102 (15.5)	< 0.01	0.26	121 (20.9)	98 (16.9)	0.10	0.10
Sepsis [% (N)]		384 (8.0)	24 (3.6)	< 0.01	0.19	346 (7.6)	20 (3.0)	< 0.01	0.2	33 (5.7)	20 (3.4)	0.09	0.11
Shock [% (N)]		53 (1.1)	4 (0.6)	0.31	0.06	42 (0.9)	2 (0.3)	0.16	0.08	7 (1.2)	2 (0.3)	0.18	0.10
Respiratory failure [% (N)]		389 (8.1)	20 (3.0)	< 0.01	0.23	328 (7.2)	17 (2.6)	< 0.01	0.22	29 (5.0)	17 (2.9)	0.10	0.11
Acute prostatitis [% (N)]		42 (0.9)	6 (0.9)	1	< 0.01	42 (0.9)	6 (0.9)	1	< 0.01	3 (0.5)	6 (1.0)	0.50	0.06
Acute tubule-interstitial nephritis [% (N)]		373 (7.8)	18 (2.7)	< 0.01	0.23	359 (7.9)	17 (2.6)	< 0.01	0.24	19 (3.3)	17 (2.9)	0.87	0.02
Cystitis [% (N)]		86 (1.8)	12 (1.8)	1	< 0.01	80 (1.8)	12 (1.8)	1	< 0.01	17 (2.9)	11 (1.9)	0.34	0.07
urinary tract disease [% (N)]		948 (19.8)	321 (47.7)	< 0.01	0.62	897 (19.7)	317 (48.2)	< 0.01	0.63	257 (44.3)	239 (41.2)	0.31	0.06
JCS [% (N)]	0	3420 (71.3)	592 (88.0)	< 0.01	0.43	3298 (72.5)	585 (88.9)	< 0.01	0.43	479 (82.6)	507 (87.4)	0.13	0.14
	I	1006 (21.0)	65 (9.7)			938 (20.6)	60 (9.1)			79 (13.6)	60 (10.3)
	II	273 (5.7)	13 (1.9)			235 (5.2)	11 (1.7)			19 (3.3)	11 (1.9)
	III	91 (1.9)	3 (0.4)			76 (1.7)	2 (0.3)			3 (0.5)	2 (0.3)
	NA	6 (0.1)	0 (0.0)			5 (0.1)	0 (0.0)			0.0 (0)	0.0 (0)
Mechanical ventilation		12 (0.3)	2 (0.3)	1	0.01	11 (0.2)	2 (0.3)	1	0.01	1 (0.2)	2 (0.3)	1.00	0.03
Dialysis		13 (0.3)	3 (0.4)	0.69	0.03	13 (0.3)	3 (0.5)	0.72	0.03	2 (0.3)	3 (0.5)	1.00	0.03
Vasopressor use		64 (1.3)	4 (0.6)	0.15	0.08	60 (1.3)	3 (0.5)	0.09	0.09	4 (0.7)	3 (0.5)	1.00	0.02

Abbreviations: BMI body mass index, JCS Japan Coma Scale, SD standard deviation, SMD standardized mean difference

Primary effectiveness outcome

Dataset 2 was used to compare the two groups in terms of days to hospital discharge. The median time to discharge was 11 days (95% confidence interval [CI] 11–11) in the cefmetazole group and 4 days (95% CI: 3–5) in the flomoxef group, with significantly fewer days in the flomoxef group (log-rank test: P < 0.001) (Fig. 4). Cox-proportional hazards analysis also revealed an HR of 1.70 (95% CI 1.56–1.85, P < 0.001) for live discharge in the flomoxef group.

Fig. 4.

Kaplan–Meier plot illustrating survival post-discharge in Dataset 2. Kaplan-Meier curves for length of hospital stay by antimicrobial agent. Kaplan-Meier plots show hospitalization rates for patients in the cefmetazole and flomoxef groups from index date to survival discharge for Dataset 2

The duration of hospital stay until discharge was evaluated using Dataset 3, following propensity score matching. In this analysis, the median time to discharge was 9 days (95% CI 8–10) for patients in the cefmetazole group, compared to 5 days (95% CI 4–6) for those in the flomoxef group. Thus, the flomoxef group experienced significantly shorter hospital stays, as evidenced even after propensity score matching (log-rank test: P < 0.001) (Fig. 5). The hazard ratio for live discharge associated with flomoxef use was 1.60 (95% CI 1.42–1.81, P < 0.001). In the sensitivity analysis conducted using the IPW method, the hazard ratio for survival to discharge associated with flomoxef was 1.41 (95% CI 1.25–1.58; P = 0.001).

Fig. 5.

Kaplan–Meier plot illustrating survival post-discharge in Dataset 3. Kaplan–Meier curves for the length of hospital stay by an antimicrobial agent. Kaplan–Meier plots show hospitalization rates for patients in the cefmetazole and flomoxef groups from index date to survival discharge for Dataset 3

Secondary effectiveness outcome

The 28-day mortality rate was 2.71% (130/4796) in the cefmetazole group and 1.34% (9/673) in the flomoxef group, and multiple logistic regression analysis showed no significant difference between the two groups (OR 1.08, 95% CI 0.53–2.21, P = 0.836). Prescriptions for carbapenems were ordered for 6.01% (288/4796) and 4.61% (31/673) in the cefmetazole and flomoxef groups, respectively (OR 1.05, 95% CI 0.70–1.57, P = 0.824) (Table 3).

Table 3.

Secondary efficacy endpoints

	Odds ratio (flomoxef/cefmetazole)	95% CI	P value
28-day mortality	1.08	0.53–2.21	0.836
Carbapenem use	1.05	0.70–1.57	0.824

Abbreviations: CI confidence interval

Safety outcome

The incidences of AEs related to the gastrointestinal, renal, and hepatic systems and hypersensitivity reactions were analysed (Table 4). Renal failure was the most reported AE in the cefmetazole group, affecting 7.5% of patients. This was followed by hepatic dysfunction, occurring in 2.3% of the cases. Furthermore, gastrointestinal AEs included C. difficile infection in 1.1% of the patients in the cefmetazole group. In the flomoxef group, renal failure (3.6%) was also the most common adverse event, followed by hepatic dysfunction (2.5%) and other forms of kidney dysfunction (0.9%). C. difficile infection (P = 0.03) and kidney failure (P = 0.04) were significantly less common in the flomoxef group than in the cefmetazole group. In the safety analysis of Dataset 3, similar to the findings in Dataset 1, the cefmetazole group showed a significantly higher incidence of kidney failure compared to the flomoxef group (P < 0.01) (Additional File 6).

Table 4.

Safety endpoints of Dataset 1

	Cefmetazole (n = 4796)	Flomoxef (n = 673)	P value
Gastrointestinal
Non-C. difficile diarrhoea [% (N)]	23 (0.5)	0 (0.0)	0.14
C. difficile infection [% (N)]	4 (0.1)	0 (0.0)	1
Kidney
Kidney failure [% (N)]	360 (7.5)	24 (3.6)	< 0.01
Other kidney dysfunction [% (N)]	54 (1.1)	6 (0.9)	0.73
Liver
Liver dysfunction [% (N)]	108 (2.3)	17 (2.5)	0.76
Hypersensitivity
Anaphylactic shock [% (N)]	0 (0.0)	0 (0.0)	NA
Rash [% (N)]	2 (0.0)	0 (0.0)	1

Discussion

This study investigated the effectiveness and safety of flomoxef compared with cefmetazole in patients with UTIs. Our analysis of the Japanese surveillance data showed that the in vitro resistance rates of third-generation cephalosporin-resistant E. coli and K. pneumoniae for flomoxef were lower than those for cefmetazole. The in vitro evaluation of the combined antimicrobial activities against an ESBL-producing multidrug-resistant strain demonstrated that both drugs exhibited similar patterns of interaction. An analysis of the claims data revealed that the length of hospital stay for patients with UTIs requiring treatment was shorter in the flomoxef group than in the cefmetazole group, with no significant difference in 28-day mortality or the rate of additional carbapenem prescriptions. The incidence rates of C. difficile infection and renal failure after therapy were significantly lower in the flomoxef group than in the cefmetazole group. Considering these data, flomoxef may be a potential treatment option for UTIs, including those caused by ESBL-producing bacteria, in clinical practice.

Cefmetazole and flomoxef both possess a structure containing a 7-α-methoxy group. This structural feature hinders access to the active site of enzymes through steric hindrance [28]. As a result, hydrolysis by β-lactamases is reduced, enabling these agents to exhibit efficacy against ESBL-producing bacteria. Indeed, treatment with cefmetazole or flomoxef may serve as an effective alternative to carbapenem therapy for bloodstream infections caused by ESBL-producing Escherichia coli [29].

To date, no adequately powered randomized controlled trials have compared the relative efficacy of cephamycin and oxacephem against infections due to ESBL-producing bacteria. Several observational studies have compared the effectiveness of a cephamycin or an oxacephem, but all had relatively small numbers of patients [30]. As a result, clinical data on the use of a cephamycin or an oxacephem for bacteria, including ESBL-producing bacteria, are scarce, and the difference in efficacy between cefmetazole and flomoxef is unknown.

The CLSI defines the MIC breakpoints for cefmetazole against Enterobacterales as ≤ 16 μg/mL: Susceptible, 32 μg/mL: Intermediate, and ≥ 64 μg/mL Resistant [31]. The JANIS data showed that flomoxef tended to have a lower frequency of MIC ≥ 64 μg/mL against 3GC-R E. coli and K. pneumoniae, including ESBL-producing bacteria, compared to cefmetazole. Indeed, a previous study reported lower MIC₉₀ values of flomoxef than those of cefmetazole against ESBL-producing E. coli and K. pneumonia [32]. These data suggest that flomoxef may be considered a viable treatment option for ESBL-producing bacteria. In addition, the findings from the DiaMOND assay support the hypothesis that flomoxef is as effective as cefmetazole, not only as a standalone treatment but also when combined with other drugs. This is important for clinical practice, as it provides flexibility in treatment strategies, especially in regions with high prevalence rates of ESBL-producing bacteria.

The JMDC claims database used in this study encompasses data from 860 facilities across Japan, which are deemed representative of routine medical practices [33]. A previous study showed that over 80% of UTIs were attributed to either E. coli or K. pneumoniae [34, 35], and this epidemiological information can be extrapolated to the JMDC claim data as well. In addition, antimicrobial susceptibility testing results for clinical isolates during the same period as the claim data analysis may reflect the resistance status in the clinical background of the claims data. Therefore, part of the effectiveness of flomoxef observed in the claims data analysis may be explained by the difference in the rate of resistance between cefmetazole and flomoxef.

This study has several limitations. First, biases might exist in the clinical decision-making regarding the choice between cefmetazole and flomoxef. While there is no definitive evidence favouring the effectiveness of cefmetazole over flomoxef, it was observed that in claim data used in the present study, cefmetazole was more frequently prescribed to patients in a more severe general condition. Second, the claims data used in this study were limited to the hospitalization of interest, and any AEs occurring after discharge from the hospital were not captured. The median length of hospital stay for flomoxef was approximately half that for cefmetazole, which may have resulted in a shorter observation period for AEs in the flomoxef group. Third, the ICD-10 codes include numerous conditions beyond N39 that suggest urinary tract infections, and relying solely on N39 may unnecessarily exclude cases of urinary tract infections. For instance, acute interstitial nephritis (ICD-10 code: N10) is also a condition that suggests urinary tract infections. However, these conditions can have multiple causes other than infections [36]. Limiting the infections that prompted the administration of cefmetazole and flomoxef to specific conditions helps homogenize the patient backgrounds in both groups and enhances comparability. Therefore, this study used only the ICD-10 code N39. Fourth, this study lacked the use of confirmatory diagnostic methods, such as CTX-M gene analysis, double-disk synergy test (DDST), ESBL/AmpC confirmation tests, and modified carbapenem inactivation method (mCIM). This prevents definitive identification of ESBL-producing strains, resulting in the possibility of coexisting AmpC β-lactamases or unresolved OXA-type β-lactamases. These factors may have introduced potential bias in evaluating the individual and combined effects of cefmetazole and flomoxef, necessitating careful consideration in data interpretation.

Flomoxef lacks sufficient pharmacological data in humans, and the CLSI breakpoint for flomoxef has not yet been defined. Despite increasing international attention on flomoxef, including its use in Global Antibiotic Research & Development Partnership (GARDP) clinical studies, information on its clinical efficacy remains limited [29, 37]. This study demonstrates that flomoxef can be a viable treatment option for UTIs comparable to cefmetazole, utilising national claim data and antimicrobial resistance surveillance data. Considering the recent shortage of critical antimicrobials, particularly β-lactam antimicrobials, in clinical settings, flomoxef is expected to be considered as a potential option against ESBL-producing bacteria, similar to cefmetazole and carbapenem antimicrobials [16, 17]. We acknowledge the importance of cost considerations in antimicrobial stewardship programs. While the brand-name drug price of flomoxef is higher than that of cefmetazole, the patent for flomoxef has expired [38]. With the accumulation of data from studies, such as ours, the utilisation of flomoxef, including its generic versions, will become more widespread.

Conclusions

The effectiveness of flomoxef may be comparable to that of cefmetazole in treating UTIs without major complications. Thus, flomoxef is a viable treatment option for UTIs in locales with a high prevalence of ESBL-producing strains. To further elucidate the therapeutic value of flomoxef as a treatment option, more comprehensive evaluations of its clinical efficacy are warranted, particularly focusing on its potential effectiveness against drug-resistant pathogens. This assessment should involve rigorous clinical studies to establish its comparative advantages in antimicrobial stewardship programs and infection control strategies.

Abbreviations

ADL

Activities of Daily Living

AE

Adverse event

AMED

Japan Agency for Medical Research and Development

BMI

Body mass index

CI

Confidence Interval

CLSI

Clinical and Laboratory Standards Institute

C. difficile

Clostridioides difficile

DPC

Diagnosis Procedure Combination

ESBL

Extended-Spectrum Beta-Lactamase

FICI

Fractional inhibitory concentration index

IC90

90% Inhibitory concentration

ICD-10

International Statistical Classification of Diseases and Related Health Problems, 10th Revision

JANIS

Japan Nosocomial Infections Surveillance

JMDC

Japan Medical Data Center

JCS

Japan Coma Scale

MIC

Minimum inhibitory concentration

OR

Odds ratio

UPEC

Uropathogenic Escherichia coli

UTI

Urinary tract infection

Authors' contributions

Data collection, Analysis, Interpretation, and Statistical analysis: TN, TK, KY, KM, YM, MI, MS1. Drafting manuscript: TN, TK, YM. Manuscript revision: TN, MG, SN, TK, KY, AH, YM, MS2, KI. All the authors have read and approved the final version of the manuscript.

Funding

This work was supported by Japan Agency for Medical Research and Development (AMED) [grant number JP23wm0325037, JP24fk0108665, JP24fk0108683, JP24fk0108712, JP24fk0108642, JP24gm1610003, JP24wm0225029, JP24wm0225022, and JP23 gm1610013] and JSPS KAKENHI Grant (23H02634, 23K27325), and Health Labour Sciences Research Grant, Ministry of Health, Labour and Welfare (25HA1004). The funders had no role in the study design; collection, analysis, and interpretation of data; writing of the report; or decision to submit for publication.

Data availability

Data will be made available upon request from the corresponding author after the approval of the proposal.

Declarations

Ethics approval and consent to participate

This part of the study was approved by the Ethics Committee of Tokushima University Hospital (protocol number: 4492).

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.