Metformin and Beyond: Individualizing Care for Low Back Pain
Phase: PHASE2
Conditions: Low Back Pain
Sponsor: Gwendolyn Sowa

Official Title:  Effects of Metformin on Low Back Pain 
ClinicalTrials.gov ID (NCT number): NCT04055012  
Document Date: 05/17/2022 
 
 

Scientiﬁc Background 
Low back pain is one of the most common musculoskeletal conditions requiring medical 
care and contributing to patient impairment and disability, with over 25% of the general 
population reporting low back pain at any given time and a lifetime incidence exceeding 
80%. However, the care of low back pain represents one of the greatest challenges facing 
musculoskeletal care today. Current care for low back pain relies on a trial and error 
approach, with increasingly aggressive options considered after each failed treatment. This 
results in exposure of patients to unnecessary risks associated with treatments that are 
unlikely to be helpful, signiﬁcant wasted resources, and delays in symptom improvement 
(1). In addition, disc degeneration is ubiquitous in our aging population (2-3), in whom 
standard treatments, including injections, surgery, and current medication options 
(particularly NSAIDs and opioids), carry increased risk. With increasing interest in the anti-
aging effects of metformin, and potential effects in the intervertebral disc related to 
inﬂammation, anabolic activity and cell senscence (4), the favorable side effect proﬁle and 
low cost make metformin an attractive therapeutic candidate for the treatment of low back 
pain. In addition, preliminary observational data in patients with low back pain taking 
metformin suggest an improvement in pain score compared to patients not taking 
metformin and over time (see below). With the suggested effects of metformin on the pain 
experience, inﬂammatory cascade (5), and microbiome (6), exploring the associations of 
these key biomarkers with response to oral metformin may reveal sub-populations of 
subjects more likely to respond to treatment as well as novel targets for future therapeutics. 
In addition, because degenerative changes and low back pain increase with age, and aging 
is associated with systemic inﬂammation, older adults may have an even greater response 
to a medication such as metformin, underscoring the potential opportunity of this 
treatment approach. 
We have previously demonstrated associations of protein and genetic biomarkers with pain 
and function in axial low back pain (7-8). In addition, we queried the UPMC data warehouse 
to compare patients with low back pain who were taking metformin vs those taking other 
medications for their diabetes management. Diabetic patients taking metformin (n=26,077) 
had slightly lower average pain scores (6.2) than diabetic patients not taking metformin 
(n=21,540) (6.4). ESR was also lower for patients taking metformin (21.2 vs 26.4). Among 
patients not taking NSAID or oral steroid, average pain scores remained in favor of 
metformin (6.1 vs 6.4). We then queried the database to examine patient pain score one 
year after initial prescription of metformin (n=26,937) and demonstrated small 
improvement in average pain score, from 6.5 to 6.2 after one year of metformin. When these 
patients were limited to patients with an ESR of 10-30 (chosen based on above ﬁnding and 
prior evidence in low back pain (9-10), the average pain score improvement widened to 6.8 
to 6.3. and was similar amongst patients without NSAID or steroid use (6.8 to 6.1). Finally, 
when subjects were further narrowed to patients with ESR 10-20, the pain score changed 
from 9 to 4, however, this resulted in extremely small sample size (n=2). These results justify 
to proposed prospective study (SA1), and also provide evidence of sub-phenotypes of 
patients who will be more likely to respond to treatment (SA2). 
 

In addition to the above data, we have previously developed a clinical prediction model for 
patients with axial low back pain for response to epidural injection. While we accurately 
predicted 22% of the total population with this model, addition of protein and genetic 
polymorphism data into the predictive model as proposed herein improved the predictive 
capacity of the model, demonstrating the feasibility of this approach. 
 
Study Objectives 
The purpose of the current study is to determine the effects of metformin in non-diabetic 
patients with low back pain, and identify novel targets for future treatments. 
Speciﬁc Aim 1: To examine the response in pain and pain related function to oral metformin 
treatment for 6 months in patients with axial low back pain. 
Hypothesis: Patients with axial low back pain treated with metformin for 6 months will 
demonstrate a 2 point or greater improvement in numeric pain rating score and be superior 
to placebo in pain and functional outcome measures. 
Speciﬁc Aim 2: To examine the associations of clinical characteristics, genetic, protein and 
microbiome biologic signatures with response to treatment, and develop a robust 
personalized predictive model for determining response. 
Hypothesis: Polymorphisms in pain perception genes, blood based protein biomarkers, and 
microbiome characteristics will show signiﬁcant associations with response to metformin 
in regard to both pain and pain related function. In addition, older patients with moderate 
levels of systemic inﬂammation will demonstrate a greater response. 
 
Study Design & Methods 
Randomized, placebo controlled, wait list controlled, clinical trial. Subjects will be 
randomized to one of the following groups: 
-High Dose Metformin Group 
-Low Dose Metformin Group 
-High Dose Placebo Group 
-Low Dose Placebo Group 
-Wait-list Control Group (will have a 3 month "wait-list" and then be randomized to 
treatment group at month 3 visit) 
Subjects will take study medication for a total of 6 months 
 
 

Eligibility Criteria 
Inclusion criteria: 
-Age 18 and above 
-Diagnosed with axial low back pain (low back pain more severe than pain in other parts of 
the body, without radiation of pain into the lower extremities). 
-Women of child bearing potential must have a negative serum pregnancy test at baseline. 
Exclusion criteria: 
-Diagnosed with rheumatoid arthritis, lupus, other autoimmune/systemic inﬂammatory 
arthropathies 
-Progressive lower extremity weakness or numbness 
-Recent oral or injected steroid use (within last 3 months) 
-NSAID use 
-Chronic kidney disease (eGFR <60) 
-Diagnosis of diabetes mellitus or elevated HbA1c at screening (> 6.5) 
-Subjects must not be pregnant or breastfeeding, or planning to become pregnant or 
breastfeed during the course of the trial 
-Unable to take an oral medication in a non crushable pill form 
-Taking metformin presently or within the last 6 months 
-History of allergy to metformin 
-History of lactic acidosis or elevated lactate at screening (> 2.2) 
-Severe Hepatic dysfunction 
-Currently taking a diabetic medication such as sitagliptin, saxagliptin, linagliptin, 
alogliptin, sitagliptin with metformin 
-Currently taking a Carbonic anhydrase inhibitor such as topiramate, zonisamide, 
acetazolamide, dichlorphenamide, methazolamide 
-Currently taking cimetidine 
 
Statistical Considerations 
Sample size is estimated based on feasibility of subject recruitment based on prior study of 
axial low back pain, as well as prior studies demonstrating clinically and statistically 
signiﬁcant change in the primary outcome of NPRS for randomized trials of NSAID in as few 
as 37-295 patients. For patients who met all inclusion criteria in our previous study 

examining epidural steroid injection for axial low back pain, our successful recruitment rate 
was 72%. For this prior study, we screened 1455 subjects over a one year period, and 768 
were excluded due to leg pain/radiculopathy. Therefore, we expect adequate availability of 
subjects to meet our recruitment goal. Formal sample size justiﬁcation based on 80% 
power, alpha = 0.05: 
Effect Sizes: 
High vs. Low: 0.79 
High vs. placebo: 0.79 
Low vs. placebo: 0.79 
Control vs. placebo: 0.86 
*These are all based on two-sample t-tests with a common variance. 
Per MOD19010007-009: While we retained data from the initial enrollment, they not be 
included in the parent statistical analysis. Therefore, this would not impact the overall 
analysis plan since re-enrolled patients would complete the new proposed baseline data 
collection (ie treated as an entirely new subject). 
Since there has been sufficient wash-out period for medication and the short time enrolled 
in the study, re-enrolling subjects is not expected to inﬂuence results