The role of traditional Chinese medicine on fracture surgery, hospitalization, and total mortality risks in diabetic patients with osteoporosis

Yi-Chen Liu; Chi-Hsiang Chung; Chien-Jung Lin; Sheng-Chiang Su; Feng-Chih Kuo; Jhih-Syuan Liu; Peng-Fei Li; Chia-Luen Huang; Li-Ju Ho; Chun-Yung Chang; Ming-Shiun Lin; Chih-Ping Lin; An-Che Cheng; Chien-Hsing Lee; Chang-Hsun Hsieh; Yi-Jen Hung; Hsin-Ya Liu; Chieh-Hua Lu; Wu-Chien Chien

doi:10.1371/journal.pone.0289455

. 2024 May 2;19(5):e0289455. doi: 10.1371/journal.pone.0289455

The role of traditional Chinese medicine on fracture surgery, hospitalization, and total mortality risks in diabetic patients with osteoporosis

Yi-Chen Liu ¹, Chi-Hsiang Chung ^2,³, Chien-Jung Lin ⁴, Sheng-Chiang Su ¹, Feng-Chih Kuo ¹, Jhih-Syuan Liu ¹, Peng-Fei Li ¹, Chia-Luen Huang ¹, Li-Ju Ho ¹, Chun-Yung Chang ⁵, Ming-Shiun Lin ¹, Chih-Ping Lin ¹, An-Che Cheng ¹, Chien-Hsing Lee ¹, Chang-Hsun Hsieh ¹, Yi-Jen Hung ¹, Hsin-Ya Liu ⁶, Chieh-Hua Lu ^1,^*, Wu-Chien Chien ^2,^3,^7,^*

Editor: Tsung-Tai Chen⁸

PMCID: PMC11065294 PMID: 38696479

Abstract

Background

Studies have confirmed that osteoporosis has been considered as one of the complications of diabetes, and the health hazards to patients are more obvious. This study is mainly based on the Taiwan National Health Insurance Database (TNHID). Through the analysis of TNHID, it is shown that the combined treatment of traditional Chinese medicine (TCM) medicine in patients of diabetes with osteoporosis (T2DOP) with lower related risks.

Methods

According to the study design, 3131 patients selected from TNHID who received TCM treatment were matched by 1-fold propensity score according to gender, age, and inclusion date as the control group. Cox proportional hazards analyzes were performed to compare fracture surgery, hospitalization, and all-cause mortality during a mean follow-up from 2000 to 2015.

Results

A total of 1055/1469/715 subjects (16.85%/23.46%/11.42%) had fracture surgery/inpatient/all-cause mortality of which 433/624/318 (13.83%/19.93%/10.16%) were in the TCM group) and 622/845/397 (19.87%/26.99%/12.68%) in the control group. Cox proportional hazards regression analysis showed that subjects in the TCM group had lower rates of fracture surgery, inpatient and all-cause mortality (adjusted HR = 0.467; 95% CI = 0.225–0.680, P<0.001; adjusted HR = 0.556; 95% CI = 0.330–0.751, P<0.001; adjusted HR = 0.704; 95% CI = 0.476–0.923, P = 0.012). Kaplan-Meier analysis showed that the cumulative risk of fracture surgery, inpatient and all-cause mortality was significantly different between the case and control groups (all log-rank p<0.001).

Conclusion

This study provides longitudinal evidence through a cohort study of the value of integrated TCM for T2DOP. More research is needed to fully understand the clinical significance of these results.

Introduction

Aging societies seeing rising rates of diabetes and osteoporosis each year can pose significant health problems for a nation’s society [1]. The global prevalence of diabetes among people aged 20–79 years is estimated to be 10.5% (536.6 million) in 2021, rising to 12.2% (783.2 million) by 2045 [2]. Osteoporosis is considered an important contributor to fractures of the spine, hip, distal forearm, and proximal humerus, which almost always result in hospitalized loss of function [3]. The classification of bone mineral density and the diagnosis of osteoporosis was established by the World Health Organization in 1994, as measured by the widely used dual-energy X-ray absorptiometry, and a T-score equal to or less than -2.5 correlates with bone mass [4]. Osteoporosis is a recognized comorbidity in patients with diabetes [5], and an important independent risk factor for osteoporosis [6].

According to the 2019 Taiwan Diabetes Yearbook, there are more than 2.2 million people with diabetes in Taiwan, and the rate of diabetes among people > 65 years of age is as high as 25% [7]. What is worrying is that, for every four people > 65 years of age, 1% have OP, while the fracture risk is increased in patients with diabetes, who are more likely to develop OP than the general population [8]. If diabetes is added as a risk factor, the probability of fractures due to osteoporosis increases further.

In Taiwan, traditional Chinese medicine (TCM) is becoming increasingly popular as an adjunctive treatment for chronic diseases, particularly diabetes [9]. Many studies to date described treating diabetes with TCM and concluded that it can improve blood sugar to a certain extent [10]. However, it is unknown whether the severity of osteoporosis of patients with type 2 diabetes and osteoporosis (T2DOP) who receive TCM treatment will decrease in terms of reduced fracture surgery, hospitalization, or mortality rates. This study aimed to analyze data from the Taiwan National Health Insurance Research Database (NHIRD) to investigate whether T2DOP plus TCM treatment could reduce the risks of fracture surgery, hospitalization, and all-cause mortality among patients with T2DOP.

Materials and methods

Data sources

Patients with diabetes mellitus and osteoporosis were recruited from the Taiwan outpatient Longitudinal Health Insurance Database (LHID). We used data from NHIRD to investigate whether TCM treatment could reduce fracture surgery, hospitalization, or mortality in diabetic patients with osteoporosis over a 15-year period (2000–2015). In 1995, Taiwan launched the National Health Insurance (NHI) program and it has contracted with 97% of medical providers in Taiwan, which has a population of approximately 23 million, or 99% of the total population of Taiwan, as of June 2009 [11]. NHIRD uses the International Classification of Diseases, Ninth Revision Clinical Modification (ICD-9-CM) to record diagnoses. All diagnoses of type 2 diabetes mellitus (T2D) and osteoporosis were made by specialist certified medical professionals, while treatment included the herbal formulae illustrated in S1 Table. The NHI randomly reviewed records for every 100 outpatient visits and every 20 inpatient claims to verify diagnostic accuracy [12].

Study design and sample participants

Our study used a retrospective paired cohort design. From January 1, 2000 to December 31, 2015, the diagnoses of T2D and osteoporosis were selected according to the codes ICD-9-CM 250.XX (T2D) and ICD-9-CM 733.0 (osteoporosis), respectively. According to these ICD-9-CM codes, each enrolled patient had at least 3 outpatient visits during the study period, and patients who received less than 3 TCM treatments and were younger than 18 years old were excluded. Covariates included Chalson Comorbidity Index (CCI) minus T2D, level of care, gender, and age. CCI represents "comorbidity" and catastrophic illness represents "severity".

We initially included 29,166 T2DOP; however, 5,136 patients were ultimately excluded because they received TCM treatment before 2000, had no follow-up records, were younger than 18 years old, or because their gender could not be identified. Finally, 24,030 T2DOP were included in the analysis, among whom 4,155 who received TCM treatment, 19,875 who did not receive TCM treatment, and 1024 outpatient follow-up patients who received TCM treatment less than 3 times were excluded. The remaining 3131 patients who received TCM treatment were divided using 1-fold propensity score matching by gender, age, and inclusion date as a control group without TCM treatment, as shown in Fig 1.

Outcome measures

We primarily track all study participants when undergo surgery for fractures, inpatient, or mortality from any cause. Based on the NHI program’s follow-up period to the end of 2015 as the outcome measure, we will see if combining it with TCM treatment can reduce the incidence of these events.

Statistical analysis

All statistical analyzes were performed using SPSS software version 22 (SPSS Inc., Chicago, IL, USA), R software version 4.3.1 (R Software Inc., San Francisco, CA, USA), and STATA software version 9 (StataCorp LLC., College Station, Texas, USA). Chi-square and t-tests were used to assess the distribution of categorical and continuous variables, respectively. Multivariate Cox proportional hazards regression analysis with a mixed effects model was used to determine the risk of fracture surgery, hospitalization, or death in T2DOP treated with TCM. We applied Schoenfeld’s global test to test the proportional hazards assumption in the Cox proportional hazards model. Cox proportional hazards model assumes that the hazards of the different strata formed by the levels of the covariates are proportional. Schoenfeld’s global test is used to test the residuals of Cox proportional model. If P > 0.05, it means that the proportional hazard assumption is not violated; in other words, the Cox proportional hazards model can be used [13,14]. Results of statistical analyzes are presented as hazard ratios (HR) and 95% confidence intervals (CI). Differences in the risk of fracture surgery, hospitalization, or death between groups receiving and not receiving TCM were estimated using the Kaplan-Meier method and the log-rank test. Statistical significance was determined using a two-tailed test with a p-value less than 0.05.

Ethics approval and consent to participate

Our research was performed in accordance with the World Medical Association Code of Ethics (Declaration of Helsinki). The Institutional Review Board of the Tri-Service General Hospital (TSGH) approved our study and waived the need for individual written informed consent (TSGHIRB No. E202316013).

Results

We included 29,166 T2DOP, and excluded 5,136 patients who received TCM treatment before 2000, those who had no follow-up records, those who were younger than 18 years old, and whose gender could not be identified, finally included 24030 T2DOP. Among them, there were 4155 patients who received TCM treatment, 19875 patients who did not receive TCM treatment, and 1024 outpatient follow-ups who received TCM treatment were excluded for less than 3 times. The remaining 3131 patients who received TCM treatment were divided by 1-fold propensity score matching by gender, age, and inclusion date as control group without TCM treatment. Among T2DOP who received TCM treatment, 433 fractures underwent surgery, 624 were hospitalized, and 318 had all-caused mortality. Among T2DOP who did not receive TCM treatment, 622 fractures underwent surgery, 845 were hospitalized, and 397 had all-caused mortality, as shown in Fig 1. T2DOP who received TCM treatment through Kaplan-Meier analysis had a lower cumulative risk of fracture surgery, inpatient, and all-caused mortality than those who did not receive TCM that show in Figs 2–4 (all log-rank p<0.001).

Baseline characteristics of the study included sex, age, comorbidities, and disease severity (Table 1). Among the 6262 T2DOP, 4212 patients (67.26%) were female, 1025 patients (32.74%) were males, and the average age of income cases was 63.50 ± 19.87 years old which 558 patients (8.91%) were younger than 50 years old, 1284 patients (20.50%) were 50–59 years old, and 4420 patients were over 60 years old (70.58%). There were no significant differences between the TCM group and the control group with respect to sex, age, catastrophic disease, revision of the Charlson comorbidity index (CCI), and covariates.

Table 1. Characteristics of study in the baseline.

TCM	Total		With		Without		P
Variables	n	%	n	%	n	%	P
Total	6,262		3,131	50.00	3,131	50.00
Gender							0.999
Male	2,050	32.74	1,025	32.74	1,025	32.74
Female	4,212	67.26	2,106	67.26	2,106	67.26
Age (years)	63.50 ± 19.87		63.44 ± 19.84		63.56 ± 19.90		0.811
Age groups (yrs)							0.999
18–49	558	8.91	279	8.91	279	8.91
50–59	1,284	20.50	642	20.50	642	20.50
≧ 60	4,420	70.58	2,210	70.58	2,210	70.58
Catastrophic illness							0.999
Without	4,934	78.79	2,467	78.79	2,467	78.79
With	1,328	21.21	664	21.21	664	21.21
CCI_R	1.02 ± 1.13		1.02 ± 1.14		1.01 ± 1.11		0.725
Level of care							< 0.001
Medical center	2,765	44.16	1,682	53.72	1,083	34.59
Regional hospital	2,150	34.33	1,035	33.06	1,115	35.61
Local hospital	1,347	21.51	414	13.22	933	29.80

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P: Chi-square / Fisher exact test on category variables and t-test on continue variables.

In Table 2, the fracture surgery rate, inpatient rate and all-cause mortality rate in the TCM group were lower than those in the control group at the end of follow-up. There were 1055 subjects (16.85%) underwent surgery due to fractures, 433 patients in the TCM treatment group and 622 patients in the control group (13.83% vs 19.87%, p<0.001); 1469 patients (23.46%) subjects were hospitalized, 624 cases in the TCM group, 845 patients in the control group (19.93% vs 26.99%, p<0.001); 715 patients (11.42%) died, 318 patients in the TCM group, 397 patients in the control group (10.16% vs 12.68%, p = 0.002). At the end of follow-up, there were no significant differences between the TCM group and the control group with respect to sex, age, catastrophic disease, revision of the CCI, and covariates. T2DOP who will receive TCM treatment have a higher proportion in the medical center (p<0.001).

Table 2. Characteristics of study in the endpoint.

TCM	Total		With		Without		P
Variables	n	%	n	%	n	%	P
Total	6,262		3,131	50.00	3,131	50.00
Fracture surgery							< 0.001
Without	5,207	83.15	2,698	86.17	2,509	80.13
With	1,055	16.85	433	13.83	622	19.87
Inpatient							< 0.001
Without	4,793	76.54	2,507	80.07	2,286	73.01
With	1,469	23.46	624	19.93	845	26.99
All-caused mortality							0.002
Without	5,547	88.58	2,813	89.84	2,734	87.32
With	715	11.42	318	10.16	397	12.68
Gender							0.990
Male	2,050	32.74	1,025	32.74	1,025	32.74
Female	4,212	67.26	2,106	67.26	2,106	67.26
Age (yrs)	74.26 ± 19.41		74.04 ± 18.86		74.47 ± 19.95		0.381
Age groups (yrs)							0.961
18–49	538	8.59	270	8.62	268	8.56
50–59	1,268	20.25	638	20.38	630	20.12
≧ 60	4,456	71.16	2,223	71.00	2,233	71.32
Catastrophic illness							0.926
Without	4,927	78.68	2,462	78.63	2,465	78.73
With	1,335	21.32	669	21.37	666	21.27
CCI_R	1.04 ± 1.16		1.05 ± 1.17		1.03 ± 1.15		0.495
Level of care							< 0.001
Medical center	2,668	42.61	1,597	51.01	1,071	34.21
Regional hospital	2,161	34.51	1,013	32.35	1,148	36.67
Local hospital	1,433	22.88	521	16.64	912	29.13

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P: Chi-square / Fisher exact test on category variables and t-test on continue variables.

Table 3 shows the factors that affect the Cox regression of fractures received surgical treatment, Inpatient and all-caused mortality. In patients who received surgical treatment for fractures, we saw that T2DOP who received TCM had an adjusted HR of 0.467 (95 CI = 0.225–0.680, P<0.001), and a lower proportion received surgery for fractures treat. In male patients, the adjusted HR was 1.239 (95 CI = 0.931–1.625, P = 0.067) without difference with female. The patients were 50–59 years old, the adjusted HR was 1.666 (95 CI = 1.112–2.304, P<0.001), the older patients were > = 60, the adjusted HR was 1.801 (95 CI = 1.144–2.410, P<0.001), and the patients with catastrophic illness had an adjusted HR of 1.898 (95 CI = 1.456–2.591, P<0.001), those with CCI_R adjusted HR 1.331 (95 CI = 1.193–1.618, P<0.001) had a higher proportion of fractures received surgical treatment. In hospitalized patients, we found that T2DOP who received TCM had an adjusted HR of 0.556 (95 CI = 0.330–0.751, P<0.001), and a lower proportion of inpatients. For male patients, adjusted HR 1.301 (95 CI = 1.026–1.510, P = 0.033), the patients were 50–59 years old, the adjusted HR was 1.276 (95 CI = 0.960–1.556, P = 0.059), older > = 60, adjusted HR 1.878 (95 CI = 1.298–2.596, P<0.001), for patients with catastrophic illness, adjusted HR 1.875 (95 CI = 1.161–2.510, P<0.001), those with CCI_R adjusted HR 1.186 (95 CI = 1.005–1.350, P = 0.047) had a higher proportion of inpatient. Similarly in all-caused mortality, T2DOP who received TCM treatment had an adjusted HR of 0.704 (95 CI = 0.476–0.923, P = 0.012), and a lower proportion of deaths. For male patients, the adjusted HR was 1.333 (95 CI = 0.975–1.816, P = 0.057), the patients were 50–59 years old, the adjusted HR was 1.454 (95 CI = 1.023–2.026, P = 0.037), for older patients > = 60, the adjusted HR was 1.880 (95 CI = 1.346–2.455, P<0.001), for patients with catastrophic illness, the adjusted HR was 2.015 (95 CI = 1.465–2.810, P<0.001), those with CCI_R adjusted HR 1.190 (95 CI = 1.087–1.324, P = 0.007) will have higher all-caused mortality.

Table 3. Factors of prognosis by using Cox regression.

Prognosis	Fracture surgery				Inpatient				All-caused mortality
Variables	Adjusted HR	95% CI	95% CI	P	Adjusted HR	95% CI	95% CI	P	Adjusted HR	95% CI	95% CI	P
TCM
Without	Reference				Reference				Reference
With	0.467	0.225	0.680	< 0.001	0.556	0.330	0.751	< 0.001	0.704	0.476	0.923	0.012
Gender
Male	1.239	0.931	1.625	0.067	1.301	1.026	1.510	0.033	1.333	0.975	1.816	0.057
Female	Reference				Reference				Reference
Age groups (yrs)
18–49	Reference				Reference				Reference
50–59	1.666	1.112	2.304	< 0.001	1.276	0.960	1.556	0.059	1.454	1.023	2.026	0.037
≧ 60	1.801	1.144	2.410	< 0.001	1.878	1.298	2.596	< 0.001	1.880	1.346	2.455	< 0.001
Catastrophic illness
Without	Reference				Reference				Reference
With	1.898	1.456	2.591	< 0.001	1.875	1.161	2.510	< 0.001	2.015	1.465	2.810	< 0.001
CCI_R	1.331	1.193	1.618	< 0.001	1.186	1.005	1.350	0.047	1.190	1.087	1.324	0.007
Level of care
Medical Center	2.336	1.842	2.930	< 0.001	2.179	1.481	2.897	< 0.001	2.250	1.605	2.921	< 0.001
Regional	1.889	1.420	2.205	< 0.001	2.053	1.450	2.846	< 0.001	1.765	1.348	2.327	< 0.001
Local	Reference				Reference				Reference

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Adjusted HR = Adjusted hazard ratio: Adjusted variables listed in the table, CI = confidence interval.

Global test, P = 0.787 (Fracture surgery), 0.649 (Inpatient), and 0.895 (All-caused mortality).

Table 4 helps us to further illustrate that T2DOP who received TCM treatment will have lower fractures rate adjusted HR 0.467 (95 CI = 0.225–0.680, P<0.001) and lower inpatient rate adjusted HR 0.556 (95 CI = 0.330–0.751, P<0.001), no matter in gender, age, disease severity or medical center, as long as T2DOP who received TCM treatment had a lower risk of receiving surgery for fracture Treatment and inpatient rate (all p<0.001). T2DOP who received TCM treatment had lower all-caused mortality, adjusted HR 0.704 (95 CI = 0.476–0.923, P = 0.012). Regardless of gender, age, disease severity, or medical center, T2DOP who received TCM treatment had lower all-caused mortality (all p<0.05). A description of the incidence rates for the main outcomes in terms of different factors, including fracture, inpatient status, and all-cause mortality stratified by variables using Cox regression is shown in S2 Table, while the average follow-up time and other information is shown in S3 Table.

Table 4. Factors of fracture surgery、inpatient、all-caused mortality stratified by variables listed in the table by using Cox regression.

TCM	Fracture surgery With vs.Without (Reference)				Inpatient With vs.Without (Reference)				All-caused mortality With vs.Without (Reference)
Stratified	Adjusted HR	95% CI	95% CI	P	Adjusted HR	95% CI	95% CI	P	Adjusted HR	95% CI	95% CI	P
Total	0.467	0.225	0.680	< 0.001	0.556	0.330	0.751	< 0.001	0.704	0.476	0.923	0.012
Gender
Male	0.472	0.228	0.690	< 0.001	0.575	0.342	0.774	< 0.001	0.717	0.483	0.934	0.017
Female	0.457	0.222	0.677	< 0.001	0.543	0.323	0.739	< 0.001	0.723	0.472	0.915	0.007
Age groups (yrs)
18–49	0.414	0.195	0.605	< 0.001	0.520	0.299	0.699	< 0.001	0.684	0.461	0.895	< 0.001
50–49	0.433	0.206	0.634	< 0.001	0.543	0.324	0.729	< 0.001	0.700	0.473	0.914	0.007
≧ 60	0.479	0.233	0.701	< 0.001	0.570	0.337	0.765	< 0.001	0.707	0.482	0.928	0.014
Catastrophic illness
Without	0.458	0.215	0.671	< 0.001	0.548	0.315	0.740	< 0.001	0.694	0.464	0.914	0.008
With	0.487	0.240	0.712	< 0.001	0.581	0.349	0.784	< 0.001	0.730	0.494	0.957	0.029
Level of care
Medical center	0.487	0.233	0.704	< 0.001	0.571	0.336	0.772	< 0.001	0.725	0.485	0.946	0.023
Regional hospital	0.467	0.225	0.682	< 0.001	0.559	0.323	0.748	< 0.001	0.700	0.471	0.918	0.009
Local hospital	0.430	0.206	0.641	< 0.001	0.522	0.298	0.708	< 0.001	0.636	0.429	0.846	< 0.001

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PYs = Person-years; Adjusted HR = Adjusted Hazard ratio: Adjusted for the variables listed in Table 3.; CI = confidence interval.

Table 5 shows the factors influencing prognosis among different TCM subgroups, as assessed using Cox regression. These factors illustrate the use of TCM in the population, including the type of TCM treatment such as herbal prescriptions, acupuncture, TCM traumatology, or a combination of herbal prescriptions. The TCM group had lower risks of fracture (adjusted HR = 0.467, 95%CI = 0.225–0.680, P<0.001), hospitalization (adjusted HR = 0.556, 95%CI = 0.330–0.751, P<0.001), and mortality (adjusted HR = 0.704, 95%CI = 0.476–0.923, P = 0.013). Information regarding the definitions of herbal formulas is shown in S1 Table.

Table 5. Factors of prognosis among different TCM subgroups by using Cox regression.

Prognosis	TCM subgroup	Population	Events	PYs	Rate (per 10⁵ PYs)	Adjusted HR	95% CI	95% CI	P
Fracture surgery	Without TCM	3,131	622	30,439.31	2,043.41	Reference
	With TCM	3,131	433	30,014.22	1,442.65	0.467	0.225	0.680	< 0.001
	Herbal formulae only	2,347	326	22,498.38	1,448.99	0.468	0.226	0.684	< 0.001
	Acupuncture only	135	20	1,294.35	1,545.18	0.500	0.242	0.729	< 0.001
	TCM traumatology only	114	17	1,092.88	1,555.52	0.504	0.243	0.734	< 0.001
	Herbal formulae + Acupuncture	297	38	2,847.09	1,334.70	0.431	0.208	0.629	< 0.001
	Herbal formulae + TCM traumatology	238	32	2,281.52	1,402.57	0.454	0.220	0.661	< 0.001
	Herbal formulae	2,882	396	27,626.99	1,433.38	0.464	0.224	0.676	< 0.001
	Acupuncture	432	58	4,141.44	1,400.48	0.453	0.219	0.660	< 0.001
	TCM traumatology	352	49	3,374.40	1,452.11	0.469	0.227	0.685	< 0.001
Inpatient	Without TCM	3,131	845	33,255.24	2,540.95	Reference
	With TCM	3,131	624	32,597.21	1,914.27	0.556	0.330	0.751	< 0.001
	Herbal formulae only	2,347	469	24,434.55	1,919.41	0.557	0.331	0.753	< 0.001
	Acupuncture only	135	26	1,405.63	1,849.70	0.538	0.319	0.726	< 0.001
	TCM traumatology only	114	22	1,186.87	1,853.61	0.539	0.320	0.727	< 0.001
	Herbal formulae + Acupuncture	297	59	3,092.25	1,908.00	0.554	0.329	0.749	< 0.001
	Herbal formulae + TCM traumatology	238	48	2,477.91	1,937.12	0.563	0.334	0.759	< 0.001
	Herbal formulae	2,882	576	30,004.71	1,919.70	0.557	0.331	0.754	< 0.001
	Acupuncture	432	85	4,497.88	1,889.78	0.548	0.325	0.742	< 0.001
	TCM traumatology	352	70	3,664.78	1,910.07	0.555	0.329	0.750	< 0.001
All-caused mortality	Without TCM	3,131	397	46,279.43	857.83	Reference
	With TCM	3,131	318	45,131.27	704.61	0.704	0.476	0.923	0.013
	Herbal formulae only	2,347	241	33,831.05	712.36	0.712	0.481	0.933	0.017
	Acupuncture only	135	14	1,945.63	719.56	0.719	0.486	0.943	0.022
	TCM traumatology only	114	10	1,643.28	608.54	0.608	0.411	0.797	< 0.001
	Herbal formulae + Acupuncture	297	28	4,281.07	654.04	0.654	0.442	0.857	< 0.001
	Herbal formulae + TCM traumatology	238	25	3,430.24	728.81	0.729	0.492	0.954	0.027
	Herbal formulae	2,882	294	41,542.36	707.71	0.707	0.478	0.927	0.013
	Acupuncture	432	42	6,226.70	674.51	0.674	0.455	0.884	< 0.001
	TCM traumatology	352	35	5,073.52	689.86	0.690	0.466	0.903	0.002

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PYs = Person-years; Adjusted HR = Adjusted Hazard ratio: Adjusted for the variables listed in Table 3.; CI = confidence interval.

Discussions

This study used NHIRD data to investigate the effect of TCM on the fracture surgery, hospitalization, and all-cause mortality rates of patients with T2DOP. Our results showed that TCM treatment is a therapeutic option that can help reduce harm among patients with T2DOP. On Cox regression, factors affecting fracture surgery, hospitalization, and all-cause mortality rates included male sex, age > 50 years, and higher disease severity. However, after receiving the TCM treatment, regardless of sex, age, and disease severity, the above-mentioned risk of fracture surgery, hospitalization, and all-cause mortality showed a statistically significant reduction on the Kaplan-Meier analysis (log-rank, P<0.001).

Both diabetes and osteoporosis are affected by aging and often coexist [8]. Studies have pointed out that patients with diabetes have an increased risk of fractures. The longer the duration of diabetes, poor blood sugar control, and the presence of diabetic vascular complications, the higher the risk of fractures, especially in patients receiving hypoglycemic drugs and those with neuropathy and retinopathy which with comorbidities are at increased risk of falls and fractures [15,16]. It has also been noted that compared with type 1 diabetes that T2D is not currently included in the fracture risk assessment tool (FRAX) used to calculate the 10-year fracture risk probability, which may be related to the fact that more than half of T2D patients are overweight or obese [17], and the impact of T2D on bone fragility is complex [18], with T2D patients generally having higher bone mineral density (BMD) than non-diabetic patients [19]. Patients with T2D often suffer from retinal macular degeneration, and one study reported that TCM Mingjing Granules can help to improve the safety and efficacy of intravitreal injections of anti–vascular endothelial growth factor in treating neovascular age-related macular degeneration [20]. This can further reduce the incidence of retinal macular degeneration in diabetic patients, a symptom which can lead to accidents such as falls and fractures due to poor vision. T2D patients with diabetic nephropathy, secondary hyperparathyroidism, and renal osteodystrophy have also been shown to be at an increased risk of fracture [21].

Despite rapid advances in the treatment of T2D, the continued increase in the incidence of T2D indicates that currently available treatments are insufficient to reduce the prevalence of diabetes [22]. Treatment of diabetes with TCM is widely used in Taiwan, and the efficacy of TCM in T2D is also recognized in China [23]. In the treatment of T2D, the research of TCM has provided a new way, and the curative effect of TCM is worthy of further research and verification [24]. A systematic review and meta-analysis of randomized controlled trials (RCT) showed that Jinlida Granules statistically and clinically reduced fasting plasma glucose, 2 hours plasma glucose and HbA1c in patients with T2D [25]. Few recent systematic review and meta-analysis of another RCT showed that the addition of the TCM in the treatment of T2D has a statistically significant effect on reducing HbA1c in Chinese adult patients with T2D [26,27].

Similar to T2D, TCM have demonstrated therapeutic potential in the treatment of osteoporosis, often in combination with western medicine [28]. More studies have shown that these TCM play an important role in the recovery of osteoporosis by regulating the immune system [29,30]. The mode of action of TCM in the treatment of osteoporosis involves multiple pathways and targets. In general, TCM functions by promoting osteogenesis and minimizing the extremely unbalanced bone turnover, exerting anti-catabolic and anabolic effects, thus improving BMD with minimal bone microarchitectural degradation [31,32]. A recent systematic review and meta-analysis of RCT illustrated the efficacy and safety of TCM in the treatment of osteoporosis [33,34]. Recent studies have shown the therapeutic potential and outlook of alternative medicine in bone conditions, which act through exerting pro-anabolic effects and anti-catabolic effects, while regulating osteoclasts and osteoblasts [31,35]. Indeed, previous investigation has shown that bone homeostasis is regulated by osteoclasts and osteoblasts together with osteocytes, bone lining cells, osteomas, and vascular endothelial cells in the bone microenvironment within the basic multicellular unit [36]. It would be informative to investigate the osteoblastic and osteoclastic effects of TCM in terms of lowering fracture, hospitalization, and mortality risks in patients with T2DOP.

The TCM Bushen-Jianpi-Huoxue (BSJPHX) decoction has been proved in animal experiments that it may prevent diabetic osteoporosis in rats through Wnt and nuclear factor-κB signaling pathways [37]. A recent study used a systematic review and meta-analysis to explore the effectiveness of TCM treatment in T2DOP [38]. It pointed out the efficacy and safety of TCM based on principle of tonifying-kidney, strengthening-spleen, and invigorating blood circulation BSJPHX has significant efficacy against T2DOP.

Through our research, patients with T2DOP who used TCM seemed to have lower fracture surgery, hospitalization, and mortality rates. The analysis identified that patients who are male, are ≥60 years of age, have catastrophic diseases, and have higher disease severity are at higher risk of fracture surgery, which shows that closer monitoring of these patients is necessary. Our research also highlights that, regardless of the patient’s sex, age, and disease severity, as long as TCM is used to treat T2DOP, a lower risk of fracture surgery, hospitalization, and all-cause death will result.

This study has several limitations that should be mentioned. Studies based on medical claims datasets are usually biased towards various clinical data, since the information on confounding factors contained in claims datasets is usually limited [39]. Patients with osteoporosis may have been missed due to the retrospective design. NHIRD did not include other residual confounders such as genetic or dietary factors and height, weight, body mass index, DEXA scores and laboratory results of the levels of bone markers such as beta-C-terminal telopeptide, tartrate-resistant acid phosphatase 5b, propeptide of type I collagen, and alkaline phosphatase. The reason why we did not use Diabetes Complications Severity Index (DCSI) is because DCSI requires biochemical index values, but the health insurance database does not have these blood drawing values [40]. In addition, the health insurance in Taiwan will not cover visits to a Chinese medicine doctor, or prescriptions for water-cooked medicine, meaning that most medical institutions will let the patient pay for the treatment at their own expense. As a result, there is no information regarding such visits in the health insurance database, meaning that the results may be underestimated. In addition, another limitation of NHIRD that cannot show the severity of diabetes or osteoporosis, but supplementary information shows that the cumulative use time of TCMs is an average of 10.76 ± 8.03 years (S2 Table), which is similar to the results of a recent study that using TCMs group follow-up time was longer than that without using TCMs group indicating that after osteoporosis is diagnosed, the use of TCMs may delay the occurrence of fractures, and the longer the use of TCMs with lower the fracture rate [41]. Furthermore, since this was a population-based study, it was not possible to elucidate the actual mechanism underlying the association between lower risks associated with T2DOP use of TCM treatments.

Conclusion

This nationwide population-based cohort study provides longitudinal evidence that the concomitant use of TCM and T2DOP treatment is associated with lower fracture surgery, hospitalization, and mortality rates. More research is needed to fully understand the clinical implications of the potential protective effects of TCM treatment for T2DOP.

Supporting information

S1 Table. Abbreviation, ICD-9-CM, and definition.

(DOCX)

pone.0289455.s001.docx^{(14.8KB, docx)}

S2 Table. Factors of fracture, inpatient, all-caused mortality stratified by variables listed in the table by using Cox regression.

(DOCX)

pone.0289455.s002.docx^{(23.1KB, docx)}

S3 Table

1. Years of follow-up. 2. Years to prognosis.

(DOCX)

pone.0289455.s003.docx^{(15.6KB, docx)}

Acknowledgments

We appreciate the Health and Welfare Data Science Center, Ministry of Health and Welfare (HWDC, MOHW), Taiwan, for providing the National Health Insurance Reseach Database (NHIRD) and the Teh-Tzer Human Medical Research in Taiwan.

Data Availability

Information is accessible through the Taiwan National Health Insurance (NHI) Bureau's National Health Insurance Research Database (NHIRD). However, adherence to the "Personal Information Protection Act" legally enforced by the Taiwanese government prohibits the public sharing of this data. For those interested in obtaining the data, the appropriate procedure involves submitting a formal proposal to the NHIRD via their website: http://nhird.nhri.org.tw. Researchers who are interested must possess valid Institutional Review Board documentation and must submit an application to the NHIRD. After undergoing a review process, there is a fee associated with obtaining database access rights. This ensures compliance with regulatory and ethical standards while facilitating the acquisition of valuable data for research purposes.

Funding Statement

This work was supported by research grants from the Tri-Service General Hospital, No TSGH-B-112020, No TSGH-E-112258 and No 801GB112258 and the Cheng Hsin General Hospital, No:CHNDMC-112-10. The sponsor has no role in study design, data collection and interpretation, decision to publish, or preparation of the manuscript.

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PLoS One. doi: 10.1371/journal.pone.0289455.r001

Decision Letter 0

Tsung-Tai Chen

27 Sep 2023

PONE-D-23-22181Association with Lowering Fracture, Inpatient and Mortality Risk in Patients of Diabetes with Osteoporosis Combined Traditional Chinese Medicine TherapyPLOS ONE

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5. Review Comments to the Author

Reviewer #1: The causes of fracture are multiple factorial. Thus, the TCM treatment reduce fracture rate may through other route. For example, improve eye function thus reduce falling events, thus reduce fracture rate. I hope the authors can have more works about this.

Reviewer #2: This study utilized a nationwide health database to analyze the use of traditional Chinese medicine (TCM) among diabetic patients with or without osteoporosis and its impact on health outcomes. This is a highly innovative research approach.

I have the following major comments for the authors:

1.In the Materials and Methods section, the author did not provide clear definitions for diabetes, osteoporosis, and health outcomes, especially considering that a claims database was used as the data source.

2.There is a lack of specific drug classification explanation for the use of TCM scientifically processed (Powdered)

3.The definition of censoring is not explicitly explained.

4.For research results not provided Incidence rates for the main outcomes.

5.There is no discussion on the selection bias and its possible impact on research results.

6.Please ensure that references cited in the text are consistent."

Reviewer #3: PONE-D-23-22181: statistical review

SUMMARY.

This is a retrospective study to test whether traditional Chinese therapy reduces the risk of fracture surgery, hospitalization and total mortality in a sample of diabetic patients with osteoporosis. The core statistical analysis relies on a battery of Cox regressions models, estimated from two propensity-score matched samples. Beside the problematic intelligibility of the paper (see specific point no. 1), there are some major issues that should be addressed.

MAJOR ISSUES

1. Propensity-score matched samples can be useful to alleviate the possible bias of retrospective studies like this one. However, the matching is successful when there are not significant differences between the groups of interest (in this case the groups with and without TCM treatments). This is unfortunately not the case in this study (see table 1) because there are relevant differences in level of care and catastrophic illness. The authors should discuss why these differences are not expected to bias the results.

2. The treatment of interest is traditional Chinese medicine, but nothing is said about this treatment. Is there a specific TCM treatment for diabetic patients with osteoporosis? How long have these patients been treated by TCM?

3. The study relies on very few covariates and quite high is the risk that unobserved confounding factors could bias the analysis. I assume that the authors did not include further covariates simply because they are not available in the dataset. Undesired effects of unobserved confounders could be alleviated by introducing random effects in the Cox regression model, a method that is available in SPSS, the software used by the authors.

SPECIFIC POINTS.

1. English. The paper has several grammar and language issues, which need to be addressed. Even the title does not seem grammatically correct to me. A title like "The role of traditional Chinese medicine on fracture surgery, hospitalization and total mortality risks in diabetic patients with osteoporosis" would sound better.

2. The Cox regression model relies on the hypothesis of proportional hazards. Could the authors provide evidence that such assumption is fulfilled by the data?

Reviewer #4: The manuscript entitled “Association with Lowering Fracture, Inpatient and Mortality Risk in Patients of Diabetes with Osteoporosis Combined Traditional Chinese Medicine Therapy” is presented. The study is potentially interesting. The methods employed for analyses were reasonable and the conclusions were justified.

There are some potential issues.

Tabels 1 and table 4, Do you have Dexa scores for Patients of Diabetes?

It was mentioned that TCM has effects on osteoporosis. Recent studies have found Therapeutic Potential and Outlook of Alternative Medicine in bone conditions via pro-anabolic effects and anti-catabolic effects and the regulation of osteoclasts and osteoblasts (for example PMID: 28325144, PMID: 31824310). It would be relevant to discuss the osteoblastic effects and osteoclastic effects of TCM and how this might affect the precited association with Lowering Fracture, Inpatient and Mortality Risk in Patients of Diabetes with Osteoporosis.

Can you include serum biomarkers of bone remodelling in these analyses? such as measurement data of b-CTX, TRAP-5b , P1NP, ALP? In this study, it was mentioned that TCM has multiple effects. Many studies have found (for example PMID: 22465238 ) bone homeostasis is regulated by osteoclasts and osteoblasts together with osteocytes, bone lining cells, osteomacs, and vascular endothelial cells in the bone microenvironment within the basic multicellular unit (BMU). It would be informative to discuss the effect of diabetes on these cell types.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

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Reviewer #1: Yes: Chen-Kun Liaw, Associate Professor, Taipei Medical University

Reviewer #2: No

Reviewer #3: No

Reviewer #4: No

**********

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PLoS One. 2024 May 2;19(5):e0289455. doi: 10.1371/journal.pone.0289455.r002

Author response to Decision Letter 0

10 Nov 2023

Dear review committee

Thank you very much for your valuable opinions. We also responded in detail bit by bit. We hope that the members can see our intentions. We also thank the members again for their suggestions to make this article more perfect.

Sincerely yours,

Wu-Chien Chien, PhD.

Attachment

Submitted filename: Response to reviewer - PONE-D-23-22181 R1.doc

pone.0289455.s004.doc^{(64KB, doc)}

PLoS One. doi: 10.1371/journal.pone.0289455.r003

Decision Letter 1

Tsung-Tai Chen

12 Dec 2023

PONE-D-23-22181R1The role of traditional Chinese medicine on fracture surgery, hospitalization, and total mortality risks in diabetic patients with osteoporosisPLOS ONE

Dear Dr. Lu,

Please submit your revised manuscript by Jan 27 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Tsung-Tai Chen

Academic Editor

PLOS ONE

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: (No Response)

Reviewer #3: (No Response)

Reviewer #4: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #2: Yes

Reviewer #3: No

Reviewer #4: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

Reviewer #3: No

Reviewer #4: N/A

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #2: Yes

Reviewer #3: No

Reviewer #4: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #2: Yes

Reviewer #3: No

Reviewer #4: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: Thank you for the author's response to the review comments. The author did not conduct an analysis regarding the correlation between severity of diabetes, osteoporosis, and the cumulative amount of traditional Chinese medicine usage. It is suggested that the author discuss the impact of diabetes, osteoporosis severity and indication bias on the study results to enhance this better of this manuscript.

Reviewer #3: PONE-D-23-22181R1: statistical review

SUMMARY. In my first review of this paper, I have raised 3 major issues and 2 specific points. Major issues no. 1 and 2 and specific issue no. 1 have been adequately addressed. However, there is problem with the remaining issues. See below.

1. I previously raised the following concern: "The study relies on very few covariates and quite high is the risk that unobserved

confounding factors could bias the analysis. I assume that the authors did not

include further covariates simply because they are not available in the dataset.

Undesired effects of unobserved confounders could be alleviated by introducing

random effects in the Cox regression model, a method that is available in SPSS,

the software used by the authors."

In the revised manuscript, the authors declare that the statistical analysis has been revised by including random effects in the model. However, the results in Table 3 and 4 are the same as in the previous version. Table 5 seems also to have been done without including random effects. I would like to see the new tables that have been obtained by a mixed effect Cox regression.

2. I previously raised some concerns about the English. Although the authors declare that the English has been revised, I still see mistakes.

Reviewer #4: This is a revised paper. The authors have addressed questions and the paper has been improved. It is acceptable for publication.

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

PLoS One. 2024 May 2;19(5):e0289455. doi: 10.1371/journal.pone.0289455.r004

Author response to Decision Letter 1

9 Jan 2024

Response:

Thank you for your suggestions.

We describe in the discussion with blue words in Line 344-351, Page 20-21.

Thank you again for pointing these out.

Reviewer #3: PONE-D-23-22181R1: statistical review

1. I previously raised the following concern: "The study relies on very few covariates and quite high is the risk that unobserved confounding factors could bias the analysis. I assume that the authors did not include further covariates simply because they are not available in the dataset. Undesired effects of unobserved confounders could be alleviated by introducing random effects in the Cox regression model, a method that is available in SPSS, the software used by the authors." In the revised manuscript, the authors declare that the statistical analysis has been revised by including random effects in the model. However, the results in Table 3 and 4 are the same as in the previous version. Table 5 seems also to have been done without including random effects. I would like to see the new tables that have been obtained by a mixed effect Cox regression.

Response:

Thank you for your suggestions.

We are sorry that the data was not updated last time. We have corrected it, as shown in red letters in the attached Table.

The parts where the correction content is modified in abstracts and results are also displayed in blue.

Thank you again for pointing these out.

2. I previously raised some concerns about the English. Although the authors declare that the English has been revised, I still see mistakes.

Response:

Thank you for your suggestions.

The files for tracking revisions include corrections related to English revisions in the article.

Thank you again for pointing these out.

Reviewer #4: This is a revised paper. The authors have addressed questions and the paper has been improved. It is acceptable for publication.

Response:

Thank you for your previous advice.

Thank you for the very kind encouragement

Attachment

Submitted filename: Response to reviewer PONE-D-23-22181.doc

pone.0289455.s005.doc^{(33.5KB, doc)}

PLoS One. doi: 10.1371/journal.pone.0289455.r005

Decision Letter 2

Tsung-Tai Chen

2 Feb 2024

PONE-D-23-22181R2The role of traditional Chinese medicine on fracture surgery, hospitalization, and total mortality risks in diabetic patients with osteoporosisPLOS ONE

Dear Dr. Lu,

1 The distribution between the experimental and control groups differs, notably in the variable "catastrophic illness." Such difference may significantly impact outcomes, urging consideration of this variable during matching procedures.

2 It is recommended to provide documentation verifying the edits made to the manuscript after revision. Some English errors persist, including for example, inaccurate descriptions in tables such as "hospital center”

(1) Inconsistencies exist regarding the terms "comorbidity" and "severity" throughout the article. Confirm that the Charlson Comorbidity Index (CCI) represents comorbidity, while catastrophic illness denotes severity.

(2) Including literature to support the revised CCI.

(3) There were many studies utilizing database-derived measure like the Diabetes Complications Severity Index (DCSI) to demonstrate severity for patients with diabetes. Please amend the "Limitations" section to reflect this aspect accurately.

4 Please explain the results of Schoenfeld's global test and what the assumptions required for proportional hazard analysis the test satisfies.

Please submit your revised manuscript by Mar 18 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Tsung-Tai Chen

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #2: Yes

Reviewer #3: (No Response)

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

Reviewer #3: (No Response)

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #2: Yes

Reviewer #3: (No Response)

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #2: Yes

Reviewer #3: (No Response)

**********

6. Review Comments to the Author

Reviewer #2: Reviewer has undergone a thorough review, and on its significant translational value. reviewer appreciate the potential impact of research and believe it deserves acceptance. this manuscript aligns with journal's standards and contributes meaningfully to the field.

Reviewer #3: (No Response)

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: No

Reviewer #3: No

**********

PLoS One. 2024 May 2;19(5):e0289455. doi: 10.1371/journal.pone.0289455.r006

Author response to Decision Letter 2

28 Feb 2024

Association with Lowering Fracture, Inpatient and Mortality Risk in Patients of Diabetes with Osteoporosis Combined Traditional Chinese Medicine Therapy

RE:PLOS ONE Decision: Revision required [PONE-D-23-22181-R2]

Lu et al.

1. The distribution between the experimental and control groups differs, notably in the variable "catastrophic illness." Such difference may significantly impact outcomes, urging consideration of this variable during matching procedures.

Response:

Thank you for your suggestions.

Following the reviewer's suggestions, we make the distributions similar between the experimental and control groups at the beginning of the analysis and displayed the faithful description based on the new figures and tables in green fonts in the article.

Thank you again for pointing these out.

2. It is recommended to provide documentation verifying the edits made to the manuscript after revision. Some English errors persist, including for example, inaccurate descriptions in tables such as "hospital center.”

Response:

Thank you for your suggestions.

We have corrected it, as shown in green fonts in the attached Table.

Thank you again for pointing these out.

3. Inconsistencies exist regarding the terms "comorbidity" and "severity" throughout the article. Confirm that the Charlson Comorbidity Index (CCI) represents comorbidity, while catastrophic illness denotes severity. Including literature to support the revised CCI. There were many studies utilizing database-derived measure like the Diabetes Complications Severity Index (DCSI) to demonstrate severity for patients with diabetes. Please amend the "Limitations" section to reflect this aspect accurately.

Response:

Thank you for your suggestions.

1. We have corrected it, as shown in green fonts in Line 215, 222 Page 13 and Line 230 Page 14.

2. The reason why we did not use Diabetes Complications Severity Index (DCSI) is because DCSI requires biochemical index values, but the health insurance database does not have them, and it has been written into the limitation in Line 340-343, Page 20 with reference 38.

Thank you again for pointing these out.

4. Please explain the results of Schoenfeld's global test and what the assumptions required for proportional hazard analysis the test satisfies.

Response:

Thank you for your suggestions.

As a result of Schoenfeld's global test, if P > 0.05, it means that the Proportional Hazard Assumption is not violated. In other words, the Cox proportional hazards model can be used. Cox proportional hazards model assumes that the hazards of the different strata formed by the levels of the covariates are proportional.

Reference as J.Natn.Sci.Foundation Sri Lanka 2009 37(1):41-5. “Use of Schoenfeld’s global test to test the proportional hazards assumption in the Cox proportional hazards model: an application to a clinical study”

Thank you again for pointing these out.

Attachment

Submitted filename: Response to reviewer PONE-D-23-22181 R2.doc

pone.0289455.s006.doc^{(36KB, doc)}

PLoS One. doi: 10.1371/journal.pone.0289455.r007

Decision Letter 3

Tsung-Tai Chen

6 Mar 2024

PONE-D-23-22181R3The role of traditional Chinese medicine on fracture surgery, hospitalization, and total mortality risks in diabetic patients with osteoporosisPLOS ONE

Dear Dr. Lu,

Please submit your revised manuscript by Apr 20 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Tsung-Tai Chen

Academic Editor

PLOS ONE

Journal Requirements:

Additional Editor Comments:

1 There may be more than one instance of grammatical issues (the reviewer just proposed an example). The editing certification is on November 4, 2023, and the manuscript has undergone several revisions after November 4, 2023. It is advisable to provide newest editing certification

2 Please include this description of Schoenfeld's global test and its underlying assumptions, inclusive of relevant literature, in the manuscript.

[Note: HTML markup is below. Please do not edit.]

PLoS One. 2024 May 2;19(5):e0289455. doi: 10.1371/journal.pone.0289455.r008

Author response to Decision Letter 3

26 Mar 2024

Journal Requirements:

Response:

Thank you for your suggestions.

We have followed the journal requirements to check all reference lists to ensure they are complete and correct.

Additional Editor Comments:

1. There may be more than one instance of grammatical issues (the reviewer just proposed an example). The editing certification is on November 4, 2023, and the manuscript has undergone several revisions after November 4, 2023. It is advisable to provide newest editing certification.

Response:

Thank you for your suggestions.

During the submission period, the manuscript has been revised after many reviewers' suggestions. We have also sent the last revised version to the English editing unit for revision, and provided the latest editorial certification. The date of completion of editing certification is Mar 14, 2024.

Thank you again for pointing these out.

2 Please include this description of Schoenfeld's global test and its underlying assumptions, inclusive of relevant literature, in the manuscript.

Response:

Thank you for your suggestions.

We have mentioned it, as shown in orange color words in Line 156-160 Page 9 in Statistical Analysis of Materials and Methods section.

Cox proportional hazards model assumes that the hazards of the different strata formed by the levels of the covariates are proportional. Schoenfeld's global test is used to test the residuals of Cox proportional model. If P > 0.05, it means that the proportional hazard assumption is not violated; in other words, the Cox proportional hazards model can be used.

With references 13 and 14.

13. SCHOENFELD D. Chi-squared goodness-of-fit tests for the proportional hazards regression model. Biometrika. 1980;67(1):145-53. doi: 10.1093/biomet/67.1.145.

14. Abeysekera WWM, Sooriyarachchi MR. Use of Schoenfeld’s global test to test the proportional hazards assumption in the Cox proportional hazards model: an application to a clinical study. Journal of the National Science Foundation of Sri Lanka. 2009. doi: 10.4038/jnsfsr.v37i1.456.

Thank you again for pointing these out.

Attachment

Submitted filename: Response to reviewer PONE-D-23-22181 R3.doc

pone.0289455.s007.doc^{(71KB, doc)}

PLoS One. doi: 10.1371/journal.pone.0289455.r009

Decision Letter 4

Tsung-Tai Chen

2 Apr 2024

The role of traditional Chinese medicine on fracture surgery, hospitalization, and total mortality risks in diabetic patients with osteoporosis

PONE-D-23-22181R4

Dear Dr. Lu,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Tsung-Tai Chen

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Table. Abbreviation, ICD-9-CM, and definition.

(DOCX)

pone.0289455.s001.docx^{(14.8KB, docx)}

S2 Table. Factors of fracture, inpatient, all-caused mortality stratified by variables listed in the table by using Cox regression.

(DOCX)

pone.0289455.s002.docx^{(23.1KB, docx)}

S3 Table

1. Years of follow-up. 2. Years to prognosis.

(DOCX)

pone.0289455.s003.docx^{(15.6KB, docx)}

Attachment

Submitted filename: Response to reviewer - PONE-D-23-22181 R1.doc

pone.0289455.s004.doc^{(64KB, doc)}

Attachment

Submitted filename: Response to reviewer PONE-D-23-22181.doc

pone.0289455.s005.doc^{(33.5KB, doc)}

Attachment

Submitted filename: Response to reviewer PONE-D-23-22181 R2.doc

pone.0289455.s006.doc^{(36KB, doc)}

Attachment

Submitted filename: Response to reviewer PONE-D-23-22181 R3.doc

pone.0289455.s007.doc^{(71KB, doc)}

Data Availability Statement

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PERMALINK

The role of traditional Chinese medicine on fracture surgery, hospitalization, and total mortality risks in diabetic patients with osteoporosis

Yi-Chen Liu

Chi-Hsiang Chung

Chien-Jung Lin

Sheng-Chiang Su

Feng-Chih Kuo

Jhih-Syuan Liu

Peng-Fei Li

Chia-Luen Huang

Li-Ju Ho

Chun-Yung Chang

Ming-Shiun Lin

Chih-Ping Lin

An-Che Cheng

Chien-Hsing Lee

Chang-Hsun Hsieh

Yi-Jen Hung

Hsin-Ya Liu

Chieh-Hua Lu

Wu-Chien Chien

Roles

Abstract

Background

Methods

Results

Conclusion

Introduction

Materials and methods

Data sources

Study design and sample participants

Fig 1. The flowchart of study.

Outcome measures

Statistical analysis

Ethics approval and consent to participate

Results

Fig 2. Kaplan-Meier for cumulative risk of fracture surgery among patients of diabetes with osteoporosis aged 18 and over stratified by TCM with log-rank test.

Fig 4. Kaplan-Meier for survival of all-caused mortality among patients of diabetes with osteoporosis aged 18 and over stratified by TCM with log-rank test.

Fig 3. Kaplan-Meier for cumulative risk of inpatient among patients of diabetes with osteoporosis aged 18 and over stratified by TCM with log-rank test.

Table 1. Characteristics of study in the baseline.

Table 2. Characteristics of study in the endpoint.

Table 3. Factors of prognosis by using Cox regression.

Table 4. Factors of fracture surgery、inpatient、all-caused mortality stratified by variables listed in the table by using Cox regression.

Table 5. Factors of prognosis among different TCM subgroups by using Cox regression.

Discussions

Conclusion

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Tsung-Tai Chen

Roles

Author response to Decision Letter 0

Decision Letter 1

Tsung-Tai Chen

Roles

Author response to Decision Letter 1

Decision Letter 2

Tsung-Tai Chen

Roles

Author response to Decision Letter 2

Decision Letter 3

Tsung-Tai Chen

Roles

Author response to Decision Letter 3

Decision Letter 4

Tsung-Tai Chen

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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