An updated analysis of opioids increasing the risk of fractures.

OBJECTIVE: To assess the relationship between opioid therapy for chronic noncancer pain and fracture risk by a meta-analysis of cohort studies and case-control studies.
METHODS: The included cohort studies and case-control studies were identified by searching the PubMed and EMBASE databases from their inception until May 24, 2019. The outcome of interest was a fracture. This information was independently screened by two authors. When the heterogeneity among studies was significant, a random effects model was used to determine the overall combined risk estimate.
RESULTS: In total, 12 cohort studies and 6 case-control studies were included. We used the Newcastle-Ottawa Scale (NOS) to evaluate the quality of the included literature, and 14 of the studies were considered high-quality studies. The overall relative risk of opioid therapy and fractures was 1.78 (95% confidence interval (CI) 1.53-2.07). Subgroup analyses revealed sources of heterogeneity, sensitivity analysis was stable, and no publication bias was observed.
CONCLUSIONS: The meta-analysis showed that the use of opioids significantly increased the risk of fracture.

Introduction

With the advancement of society, the number of elderly people has gradually increased. Pain is a common symptom in the elderly population, and the incidence of chronic pain ranges from 25% to 76% [1]. Opioids provide effective analgesic effects in a range of persistent noncancer pain conditions and are widely used for the treatment of noncancer pain due to their analgesic and psychoactive effects [2]. There are many side effects of using opioids, such as dizziness, hypogonadism, and inhibition of the innate and acquired immune system. These side effects can lead to fractures. Vestergaard et al. [3] revealed that opioid-induced fractures may be associated with vertigo in patients after opioid use. Grey et al. [4] also confirmed that opioids cause fractures and that opioids act on the gonads to reduce bone density [4].

In addition, studies have shown that opioid-induced fractures are associated with time of use [5] and are also associated with the use of opioids [6]. Opioids have been linked to the occurrence of fractures [2,3,7-11], and although the use of opioids has been reported to increase the risk of fractures, the trend of using opioids continues to increase [12]. However, in the previous studies, due to the influence of sample size, types of research, etc., there may have been inconsistencies, and we aimed to reconfirm the correlation between opioids and fracture risk while incorporating subsequently published studies.

Materials and methods

Search strategy and data sources

A search was conducted from the inception of the PubMed and EMBASE databases until May 20, 2019, to find relevant research that met the requirements. We also searched the bibliographies of relevant articles to identify additional studies. We used the following search terms: (i) fracture ? [Title/Abstract] OR “Fractures, Bone”[Mesh]; (ii) opioid ? [Title/Abstract] OR “Analgesics, Opioid”[Mesh].

Study selection

Studies were considered eligible if they met all of the following criteria: (i) presented original data from the study; (ii) evaluated the association of opioid use with fracture incidence; (iii) had opioids as the exposure of interest; and (iv) provided hazard ratios and odd ratios (HRs and ORs) or the adjusted relative risks (RRs) and the corresponding 95% confidence intervals (CIs). If the data were duplicated or the population was studied in more than one study, we included the study with the largest sample size and the most comprehensive outcome evaluation.

Data extraction

Two investigators (YQN, ZXG) independently evaluated the eligibility of the studies retrieved from the databases based on the predetermined selection criteria. In addition, a cross-refer ence search of eligible articles was conducted to identify studies not found in the computerized search. These two authors independently extracted the following data: the first author’s name; year of publication, patient ages, sample size, study regions, years of follow-up, study design, HR, OR or RR and the 95% CIs, and statistical adjustments for confounding factors. Any disagreements were resolved either by discussion or in consultation with the co-corresponding author (TZW). The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of the research [13].

Statistical analyses

Our primary objective was to evaluate the use of opioids and the increased risk of fractures. We calculated total RR and 95% CI from the adjusted RRs, ORs or HRs and 95% CIs reported in the studies. ORs and HRs were considered to correspond to RRs. Using the Cochran Q and I2 statistic to assess statistical heterogeneity [14], we also calculated the P value of the q test representing heterogeneity; if the P value was less than 0.10, there was heterogeneity among the studies. The fixed effects model was applied when I2 <50% [15], otherwise, the random effects model was applied [16]; to further explore the source of heterogeneity, we also examined the study design, the study area and subfamily analysis of fracture types (i.e., any fracture, nonspine fracture, hip fracture). Additionally, Begg's rank correlation test and Egger's linear regression test were conducted to assess the extent of potential bias [17]. Finally, we conducted a sensitivity analysis to assess the stability of the analytical results by excluding each study to explore the impact of individual studies on the overall outcome [18]. The data analyses were conducted using STATA statistical software version 12.0 (STATA Corp. LLC, College Station, TX, USA).

Results

Literature search and study characteristics

Using predefined search strategies and inclusion criteria, a total of 18 studies were included and 1,134 articles of unrelated literature were excluded (from a total of 600 articles from PubMed and 552 articles from EMBASE) after a detailed reading of the title, abstract, and full text, and the 18 articles included 884054 participants [3,7,9,19-32]. The detailed process of inclusion in this study is shown in Fig 1. Five studies were from the United States [12,21,23,24,26,32], three from Canada [9,19,28], two from the United Kingdom [18,27], one study was from Australia, and the remaining came from European countries; 12 articles were from cohort studies, and six were from case-control studies. The study information is shown in Table 1.

Fig 1

Inclusion of literature search flow chart.

Table 1

Basic characteristics of the 18 included studies.

Author, year,	Age,	Fracture type	Study design	Sample size	Follow-up	Models	Adjustment for	NOS
location	years	/assessment			time		covariates
Jensen, 1991, Denmark	>59	hip/WHO code 820	Case-control	400	from April to December 1988	Cornfield’s iterative method	Age, sex, nursing home residency and number of hospital admissions	6
Shorr, 1992, Canada	≥65	hip/ ICD-8, ICD-9	Case-control	28541	from 1997 to 1985	Unconditional logistic regression	Age, sex, home, hospital discharge in preceding year, index year	7
Guo, 1998, Sweden	≥75	hip/ICD-9	Prospective cohort	1608	4.4 years	Cox proportional hazards	Age, sex, education, residence, ADL limitation, cognitive impairment, history of stroke and tumors	8
Ensrud, 2003, USA	≥65	fractures/ radiology reports	Prospective cohort	8127	4.8 years	Cox proportional hazards	Age, sex, race, health status, smoking, walking exercise, functional impairment, cognitive function, depression, weight change	9
Card, 2004, UK	NA	hip/NA	Prospective cohort	99467	7.3 per 10000 person-years	Cox regression	Age, sex, practice, corticosteroid use	6
Sachin, 2006, USA	≥65	hip/ICD-9	Prospective cohort	362503	464 days	Cox regression	Age, sex, use of antidepressants, antipsychotics, anxiolytics/hypnotics	7
Vestergaard, 2006, Denmark	43.44 ± 27.39	hip/NA	Case-control	42065	during 2006	Conditional logistic regression	Use of other drugs	6
Kathleen, 2010, USA	≥60	fractures/ ICD-9	Prospective cohort	2341	32.7 months	Cox proportional hazards	Age, gender, smoking, depression, substance abuse, dementia, comorbidity, prior fracture, pain site, antidepressant use, sedative use, HRT/bisphosphonate use	9
Miller, 2011, USA	≥65	fractures/ ICD-9	Retrospective cohort	17310	451 per 1000 person-years	Cox proportional hazards	Age, sex, diabetes, stroke, osteoarthritis, comorbidity index, stroke, diabetes	6
Vestergaard, 2012, Denmark	45 to 58	Fractures /X-ray	Prospective cohort	2016	10 years	Cox proportional hazards	Age, HT, BMI, baseline spine bone mineral density (BMD), family or prior fracture, serum 25-hydroxy-vitamin levels and smoking	9
Laura, 2013, USA	≥58.73 ±13.43	lower extremity /ICD-9	Retrospective cohort	7447	3–8 years	Cox proportional hazards	Age, race, completeness of spinal cord injury (SCI) level and duration of SCI	7
Lin Li, 2013, UK	18 to 80	fracture/NA	Nested case-control	71538	from 1990 to 2008	Conditional logistic regression	Smoking, BMI, comorbidities. Number of general practice visits recorded during the years before index date	7
Kristine, 2014, Sweden	≥75	hip/codes S72.0, S72.1, S72.2	Retrospective cohort	38407	during 2006	Multivariate logistic regression	Age, gender and morbidity level	8
Leach, 2015, Australia	>65	hip/ICD codes S72.0 or S72.1	Case-crossover	8828	from 2009 to 2012	Conditional logistic regression	NA	8
Acurcio, 2016, Canada	76.33 ±10.04	fracture/ICD-9, ICD-10	Retrospective nested case-control	9769	from 2007 to 2012	Conditional logistic regression	Age, sex, measures of comorbidities, history of arthroplasty, corticosteroid use, biologic agents or traditional disease-modifying antirheumatic drugs (DMARDs), use of other drugs potentially influencing the risk of fractures or falls, measures of health care resource use	7
Grewal, 2018, Canada	≥65	fracture/ICD-10	Retrospective cohort	89897	3 months	Cox regression	Age, sex, past medical history, health care use, etc.	7
Taipale, 2018, Finland	NA	hip fracture/ ICD-10	Retrospective matched cohort	70718	5 years	Cox proportional hazard	Age, sex, time since Alzheimer's disease (AD) diagnosis, socioeconomic position, university hospital catchment area, use of drugs, comorbidities	9
Vakharia, 2019, USA	≥64	fracture/ICD-9 (81.54) codes 304.00–304.02 and 305.50–305.52.	Retrospective matched cohort	23072	from 2005 to 2014	R Statistical analysis	Age, sex, use of drugs	7

Main analysis

There was a positive correlation between the use of opioids and fractures (RR 1.78, 95% CI 1.53–2.07) (Fig 2), and we observed significant heterogeneity among the studies. Eleven studies provided data on opioid use and hip fracture risk [3,7,19-23,27,29-31]. Pooled studies showed that the use of opioids had a significant impact on the risk of hip fracture (RR 1.56, 95% CI 1.37–1.79), and there was significant heterogeneity among the studies (P = 0.000, I2 = 83.1%) (Fig 3); we subsequently revealed the sources of heterogeneity through subgroup analyses.

Fig 2

Forest plot of RR with 95% CI for opioid use and fracture risk.

Fig 3

Forest plot of RR with 95% CI for opioid use and hip fracture risk.

Subgroup meta-analysis

We performed a subgroup analysis based on the type of study, region, and fracture type, and the risk of fractures was positively correlated with the use of opioids (Table 2). Subgroup analyses showed a significant increase in fracture risk after opioid use, with no statistical heterogeneity among studies conducted in the European region, Britain, and Denmark (Fig 4). Although Shorr et al. [19] was a case-control study, the control data were derived from the hospital database, which make ita retrospective study together with the studies of Miller, Laura, Grewal, Kristine and Vakharia et al. [9,24,26,29,32]. To determine the impact of these retrospective studies, we conducted further analyses without the above studies, and the overall results showed that heterogeneity significantly decreased.

Table 2

Subgroup analyses of the association between opioid use and fracture risk.

	Factor	No. of studies	RR (95% CI)	Heterogeneity P (I2%)
Study design	Case-control	6	1.57 (1.23, 2.02)	0.000 (95.6)
	Prospective cohort	6	1.62 (1.31, 2.02)	0.003 (72.5)
	Retrospective cohort	6	2.32 (1.69, 3.19)	0.000 (93.0)
Fracture type	Hip fracture	9	1.62 (1.41, 1.87)	0.000 (81.3)
	Nonspine fracture	2	2.03 (1.00, 4.13)	0.000 (95.1)
	Any fracture	7	1.97 (1.43, 2.69)	0.000 (93.5)

Fig 4

Forest plot for a subgroup meta-analysis by region.

Sensitivity analysis

To assess the stability of our results, based on the original data, sensitivity analyses were performed using a strategy that systematically excluded individual studies. In the end, there was no change in the overall results (Fig 5).

Fig 5

Sensitivity analysis of the association between opioid use and fracture risk.

Publication bias

No evidence of publication bias was found based with Begg’s rank correlation test (p>|z| = 0.649) or Egger’s linear regression test (p>|z| = 0.067) (Figs 6 and 7).

Fig 6

Begg's funnel plot.

Fig 7

Egger's publication bias plot.

Discussion

The trend of population aging is becoming more pronounced, and most of the fracture patients are elderly individuals. The elderly population has a higher fracture rate due to lower bone density. Elderly individuals are more likely to be in poor physical condition, most of them have a history of chronic pain resulting in a history of taking opioids, and the probability of fractures increases. Therefore, the incidence of fractures caused by opioids is discussed below. There is a high potential for associations between opioids and fractures.

In this meta-analysis, we included the latest basic research. The types of studies included in this analysis included case-control studies, the sample size was increased, and the study area was refined. The results showed that the use of opioids increased the risk of fracture. Previously, the most recent meta-analysis (Ping et al. [33]) was limited to the study of hip fractures, and Grewal et al. [9] showed that patients taking opioids had a risk of fracture after discharge compared with patients who were not taking opioids. The main reason for the increase was that patients taking opioids were prone to vertigo and falls that can lead to fractures. In addition, Aspinall's et al. [6] study showed that patients receiving opioid therapy had an increased risk of falls, and the accompanying final outcomes were fractures [6]. Schwarzer et al's [8] study also suggested that when opioid use was considered, the risk of fractures increased [8]. The above studies are consistent with our final results and support our findings. In addition, there are two main mechanisms for the occurrence of fractures with opioid use. One mechanism is that opioids may reduce bone density by inhibiting the production of endogenous sex hormones, leading to an increased risk of fractures [34]; the other mechanism involves the side effects of opioids, such as the central nervous system side effects of vertigo, fatigue, etc., that lead to the occurrence of fractures [7,9,27,28], and there is a high incidence of side effects, including acute cognitive deterioration, increased sputum production, decreased oxygen saturation, and constipation, after the use of opioids in elderly populations, as confirmed in recent studies [35]. The trend of the population aging is becoming increasingly pronounced, and osteoporosis in this aging population is a serious concern. The use of opioids in this population leads to more frequent fractures.

The relationships among opioids, analgesia and fracture have been examined, and we have previously published relevant articles [36]. However, for the present analysis, we included cohort studies and case-control studies, in which patients were followed up over a long time. Most of the research was of high quality, the sample sizes were large enough, and the outcome evaluations were reliable and comprehensive. In addition, although our overall analysis showed heterogeneity, we determined the source of the heterogeneity through subgroup analyses. For example, Shorr, Grewal, Miller, and Laura were all retrospective studies [9,19,24,26]. In the subgroup analysis, heterogeneity was significantly reduced suggesting that these retrospective cohort studies may have been a source of heterogeneity. Based on a regional subgroup analysis, we found that the research conducted in Canada and the United States made an important contribution to the heterogeneity (Fig 5). Therefore, we believe that geography is one of the important reasons for the heterogeneity. Next, we individually examined the heterogeneity in the Canadian group of studies. When we excluded the study by Shorr et al. [19], we found that there was no heterogeneity among the Canadian group of studies (I2 = 0.0%, p = 0.470) and in the hip fracture group of studies. Regarding the larger source of heterogeneity, we finally found the source through analysis and mainly identified the role of retrospective cohort studies and case-control studies. This comprehensive analysis suggested that heterogeneity mainly comes from retrospective articles and may also be caused by other factors, such as geographical factors, and we will continue to pay attention to these factors in the future.

Although our research has many advantages, it also has shortcomings. First, due to language limitations, the included studies were limited to English, and these language limitations may have led to studies not being included, resulting in a dataset that was not quite comprehensive. Second, some studies that are not statistically significant or have negative findings may not have been published because they were rejected by the journal or because the researcher was unwilling to submit such a publication. We also performed a publication bias test, but it is also possible that the effect value was overestimated when studies with a large degree of heterogeneity were combined. Again, the degree of control over confounding variables, such as age and gender, varied from study to study. In our meta-analysis, the timing and dose of the drug could not be studied because the time frames were different across studies. Thus, we were unable to unify the timing, and the drug dose was also different based on varying classification criteria and could not be further studied. Finally, the study participants were all Westerners, and the influencing factors were complex and variable. Therefore, we should pay attention to the global situation in these populations to improve and validatethe conclusions. It was also impossible to conduct further analyses as to whether the length of metabolism for a particular drug was an influencing factor, and this issue is worthy of attention in the future. We have included a number of different studies covering a wide range clinical and experimental factors and the results were still stable, and we will conduct a more comprehensive analysis when future conditions permit.

Conclusions

Taken together, we included different types of studies, and the results still indicated that the use of opioids significantly increased the risk of fracture. Further research, including well-designed international trials, studies of the mechanisms by which opioid use causes fractures, and studies aimed at preventing such fractures require more evidence from clinical practice.

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26 Sep 2019

PONE-D-19-19172

An updated analysis of opioids increasing the risk of fractures

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Reviewer #1: Yue et al. intended to perform meta-analysis to assess the relationship between opioid therapy for chronic non-cancer pain and fracture risk. They analyzed 18 studies including 14 classified as high-quality studies. The results showed that the use of opioid therapy and fractures was significantly associated.

1. Line 64. Authors mentioned that there have been inconsistencies association results between risk of fractures and opioid use. However, only positive result was cited with reference. Negative results should be cited to support their argument. if no negative results were reported, their motivation will be invalid and leaves the contribution of this work questionable.

2. Please define fracture in the text as well. i.e. what type of fractures were considered in this study? Different fracture may have different mechanisms.

3. What’s NOS in Table 1? The abbreviation needs to be spelled out somewhere with explanation.

4. Table 1. Need to provide the reference citation for each paper as well.

5. Figures. Footnotes are needed. e.g. what’s ES, Weight and so on?

6. As there are so many factors different from one study to another, driving high heterogeneity, it’s questionable to perform the analysis across all studies as primary analysis.

Reviewer #2: All the active drugs on the central nervous system (CNS) administered to osteoporotic elderly patients can determine fall-related injuries. Often falls have many different causes resulting from the interactions between intrinsic or extrinsic risk factors. The intrinsic risks as functional impairment or balance disorders represent the common features of the frail elderly osteoporotic patient. The extrinsic risks are often linked to treatment as the adverse drug reaction. Several studies have documented that there is a relation between falling and the number of drugs used. Drugs with central nervous system (CNS) side effects, such as benzodiazepines, antidepressants, neuroleptics, anticonvulsants and opioids are known to increase the risk of fractures and fall-related injuries. Frequently the CNS effects of opioids happen

starting opioid therapy or during substantial dose escalation.

Almost always after a few days of treatment, opioids tolerance relives CNS symptoms. Although opioids can be

essential in the treatment of moderately severe chronic pain.

Reviewer #3: Introduction

Line 54-55: It is worth including “gut dysfunction” as one of the side effects of opioid use.

Line 55-56: The authors sate that “These side effects can lead to fractures”. This sentence is spurious. Should briefly elaborate how the side effects could increase fractures or be associated with fractures.

The rationale for the study in the introduction is poorly described and there is a huge lack of logical flow in this section. The introduction should be re-written nailing the urge for an update, with valid references.

Methods & Results

I wonder why authors of this manuscript has only limited the search for two databases given the prevalence of evidence in this field.

I’m afraid that the search terms used will not assist in capturing all research in this context. I suggest to re-run the search using the word “pain” as well.

The selection criteria for the studies are poorly elaborated and the reader is not helped on how the studies have been selected for the analysis. The flow of logical consistency is lost while progressing from one paragraph to the other.

I would strongly encourage the authors to re-write the methods section in accordance to current scientific standards

The PRISMA flow diagram should be revised. The terminology used in each stage of the process is not current. For instance, “removal of literature from reading headings” should be termed as” Title exclusion”; “removal of repeat literature” should be termed as “removal of duplicates”

Authors have used Table 1 to describe the study characteristics, however, the representation of this table is not up to the expected standard. Needs revision. The font and size of the text in the table is not comparable to the text in the manuscript.

Discussion

The discussion doesn’t read well, and the flow doesn’t seem logical and not connected to the method section very well. Therefore, I recommend redoing the discussion section as well.

General points,

• The methodological reporting mars the study quality

• The reference cited is not support of the findings reported

• Authors really do need to take care of the technical words used in the manuscript.

• There are grammar mistakes and typos throughout the manuscript, and I would encourage the authors to get support from a native English speaker to improve the clarity of the language.

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Reviewer #2: Yes: Renato Vellucci

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4 Nov 2019

Dear Editor,

We are truly grateful to you and the other reviewers for the critical comments and thoughtful suggestions. We have made careful modifications to the original manuscript based on these comments and suggestions, and all changes made to the manuscript are in red,and the modified and unmodified files are named 'Revised Manuscript with Track Changes'、 'Manuscript' upload. Our financial disclosure has not changed.. We hope the revised manuscript will meet your journal’s standard. Below you will find our point-by-point responses to the reviewers' comments:

Journal Requirements:

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Response: Thank you for your comment. We has been read the relevant requirements of your magazine again, and adjusted the uploaded file name, image format, manuscript requirements, etc. one by one to meet the relevant requirements of your magazine. I hope that our adjustments will reduce unnecessary trouble for editors and reviewers.

2.We note that you have reported significance probabilities of 0 in places. Since p=0 is not strictly possible, please correct this to a more appropriate limit, eg 'p<0.0001'.

Response: Thank you for your comment. We have changed the 'p=0.000' to a more appropriate limit, eg 'p<0.0001'.

3.We noticed you have some minor occurrence(s) of overlapping text with the following previous publication(s), which needs to be addressed:

https://doi.org/10.1371/journal.pone.0128232

Response: Thank you for your comment. In our new manuscript, we have solved the problem of a slight overlap with the previous article.

Reviewers' comments:

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

Response:Thank you for your comment.We conduct our research in strict accordance with the standards of current scientific research. And deal with statistical data objectively.

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

Response:Thank you for your comment.In the data processing, we seek truth from facts and strictly follow the objective principles of statistical analysis. If there is a flaw, we sincerely hope to receive your opinion again.

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

Response:Thank you for your comment.The authors have completely disclosed all the data in their manuscripts.

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

Response:Thank you for your comment.When we finished the manuscript, we got help from a native English speaker.

5.Review Comments to the Author

Response:Thank you for your comment.The reviewers gave us the best advice, and we did find out the shortcomings of our existence from the opinions or suggestions of the reviewers. We have also briefly explained the above issues, and sincerely thank all the reviewers.

Reviewer #1:

1.Line 64. Authors mentioned that there have been inconsistencies association results between risk of fractures and opioid use. However, only positive result was cited with reference. Negative results should be cited to support their argument. if no negative results were reported, their motivation will be invalid and leaves the contribution of this work questionable.

Response:Thank you for your comment.In the latest manuscript, we have cited references to negative results.

2.Please define fracture in the text as well. i.e. what type of fractures were considered in this study? Different fracture may have different mechanisms.

Response:Thank you for your comment.In the latest manuscript, we redefine the type of fracture. The specific content we have stated in the introduction.

3.What’s NOS in Table 1? The abbreviation needs to be spelled out somewhere with explanation.

Response:Thank you for your comment.The abbreviation of NOS in Table 1 refers to Newcastle-Ottawa Scale. We have already explained below in Table 1.

4.Table 1. Need to provide the reference citation for each paper as well.

Response:Thank you for your comment.In our latest manuscript, we have provided a reference citation for each article in Table 1.

5.Figures. Footnotes are needed. e.g. what’s ES, Weight and so on?

Response:Thank you for your comment.The numbers and footnotes in the picture have been provided to the latest attachments.

6.As there are so many factors different from one study to another, driving high heterogeneity, it’s questionable to perform the analysis across all studies as primary analysis.

Response:Thank you for your comment.First, two types of research we have included are observational studies.Second, in our research events, the incidence is small,Most of studies were of high quality.Finally, there are certain deficiencies in our approach, such as research bias, confounding effects, etc., but we focus on the source of heterogeneity and ultimately determine that the type of research is not the main source of heterogeneity. For this issue, we will carry out deeper research. Thank you again for your advice.

Reviewer #2:

Response:Sincerely thank you for your comments.In the future, we will continue to pay attention to the risk relationship between central nervous system drugs and other drugs and fall-related fractures. And further concerned about the impact of the starting dose of the drug, the time of the drug.

Reviewer #3:

Introduction

1.Line 54-55: It is worth including “gut dysfunction” as one of the side effects of opioid use.

Response:Sincerely thank you for your comments.We have listed “gut dysfunction” as one of the side effects of opioids as required.

2.Line 55-56: The authors sate that “These side effects can lead to fractures”. This sentence is spurious. Should briefly elaborate how the side effects could increase fractures or be associated with fractures.

Response:Sincerely thank you for your comments.In the latest manuscript, we have briefly described the relationship between opioid side effects and fractures.

3.The rationale for the study in the introduction is poorly described and there is a huge lack of logical flow in this section. The introduction should be re-written nailing the urge for an update, with valid references.

Response:Sincerely thank you for your comments.After carefully reading the introduction, we added valid references and re-written them. Thank you again for your advice.

Methods & Results

1.I wonder why authors of this manuscript has only limited the search for two databases given the prevalence of evidence in this field.

Response:Sincerely thank you for your comments.At the beginning, the authors of the manuscript believed that the literature in the two databases was comprehensive, but we used the reviewers' comments to re-search the other three databases (Cochrane; Ovid; Web of Science).

2.I’m afraid that the search terms used will not assist in capturing all research in this context. I suggest to re-run the search using the word “pain” as well.

Response:Thank you for your comment.After listening to your suggestion, we added the word "pain" to PubMed; EMBASE; Cochrane; Ovid; Web of Science's five major databases for re-search, but the number of studies we eventually included did not change.

3.The selection criteria for the studies are poorly elaborated and the reader is not helped on how the studies have been selected for the analysis. The flow of logical consistency is lost while progressing from one paragraph to the other.

Response:Thank you for your comment.We have redefined the inclusion criteria for the study. The details are presented in our latest manuscript.

4.I would strongly encourage the authors to re-write the methods section in accordance to current scientific standards

Response:Thank you for your comment.We have rewritten the method section and hope that you can give valuable feedback again.

5.The PRISMA flow diagram should be revised，. The terminology used in each stage of the process is not current. For instance, “removal of literature from reading headings” should be termed as” Title exclusion”; “removal of repeat literature” should be termed as “removal of duplicates”.

Response:Sincerely thank you for your comments.We have changed the "removal of literature from reading headings" to "title exclusion"; "removal of repeat literature" to "removal of duplicates" in PRISMA.

6.Authors have used Table 1 to describe the study characteristics, however, the representation of this table is not up to the expected standard. Needs revision. The font and size of the text in the table is not comparable to the text in the manuscript.

Response:Sincerely thank you for your comments.We have re-edited the format and fonts of Table 1 as required. The revised Table 1 is in our latest manuscript.

Discussion

The discussion doesn’t read well, and the flow doesn’t seem logical and not connected to the method section very well. Therefore, I recommend redoing the discussion section as well.

Response:Sincerely thank you for your comments.After discussing with other authors, we rewrote the discussion. Make sure that the discussion and method parts are more closely linked and more logical. Thanks again for your advice.

General points

• The methodological reporting mars the study quality；

• The reference cited is not support of the findings reported；

• Authors really do need to take care of the technical words used in the manuscript.；

• There are grammar mistakes and typos throughout the manuscript, and I would encourage the authors to get support from a native English speaker to improve the clarity of the language.

Response:Sincerely thank you for your comments.After discussing with all the authors, we adopted the suggestions of the reviewers and carefully and carefully revised the articles. The grammatical errors in the manuscripts were also corrected. I hope that our modifications are effective. We sincerely look forward to your reply.

We look forward to receiving your reply.

Yours sincerely,

Zhaowei Teng

Submitted filename: Response to Reviewers.doc

Click here for additional data file.

9 Mar 2020

An updated analysis of the increased risk of fractures with opioids

PONE-D-19-19172R1

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27 Mar 2020

PONE-D-19-19172R1

An updated analysis of the increased risk of fractures with opioids

Dear Dr. Teng:

I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

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