Open Collections

UBC Faculty Research and Publications

Micro-structural bone changes in early rheumatoid arthritis persist over 1-year despite use of disease… Feehan, Lynne M; Li, Linda L; McKay, Heather A Dec 11, 2017

Your browser doesn't seem to have a PDF viewer, please download the PDF to view this item.

Item Metadata

Download

Media
52383-12891_2017_Article_1888.pdf [ 1.21MB ]
Metadata
JSON: 52383-1.0361790.json
JSON-LD: 52383-1.0361790-ld.json
RDF/XML (Pretty): 52383-1.0361790-rdf.xml
RDF/JSON: 52383-1.0361790-rdf.json
Turtle: 52383-1.0361790-turtle.txt
N-Triples: 52383-1.0361790-rdf-ntriples.txt
Original Record: 52383-1.0361790-source.json
Full Text
52383-1.0361790-fulltext.txt
Citation
52383-1.0361790.ris

Full Text

RESEARCH ARTICLE Open AccessMicro-structural bone changes in earlyrheumatoid arthritis persist over1-year despite use of disease modifyinganti-rheumatic drug therapyLynne M. Feehan1,2* , Linda L. Li1,2 and Heather A. McKay3AbstractBackground: We used High Resolution – peripheral Quantitative CT (HR-pQCT) imaging to examine peri-articularbone quality in early rheumatoid arthritis (RA) and explore whether bone quality improved over 12-months inindividuals receiving care consistent with practice guidelines.Methods: A 1-year longitudinal cohort study (Baseline and 12-months) evaluating individuals with early RAcompared to age/sex-matched peers. Personal demographic and health and lifestyle information were collected forall. Whereas, active joint count (AJC28), functional limitation, and RA medications were also collected for RAparticipants. HR-pQCT imaging analyses quantified bone density and microstructure in the Metacarpal Head (MH)and Ultra-Ultra-Distal (UUD) radius at baseline and 12-months. Analyses included a General Linear Modellingrepeated measures analyses examined main effects for disease, time, and interaction on bone quality.Results: Participants (n = 60, 30 RA/30 NRA); 80% female, mean age 53 (varying from 21 to 74 years). At baseline, RAparticipants were on average 7.7 months since diagnosis, presenting with few active joints (AJC28: 30% none,remaining 70% Median 4 active joints) and minimal self-reported functional limitation (mHAQ-DI0–3: 0.56). Atbaseline, 29 of 30 RA participants had received one or more non-biologic disease-modifying anti-rheumatic drugs(DMARD);13 in combination with glucocorticoid and 1 in combination with a biologic medication. One participantonly received glucocorticoid medication. Four RA participants withdrew leaving 26 pairs (n = 52) at 12-months; 23pairs (n = 46) with UUD and 22 pairs (n = 44) with MH baseline and 12-month images to compare. Notable RA/NRAdifferences (p < 0.05) in bone quality at all three sites included lower trabecular bone density and volume, morerod-like trabeculae, and larger and more variable spaces between trabeculae; fewer trabeculae at the UUD and MH2sites; and lower cortical bone density and volume in the MH sites. Rate of change over 12-months did not differbetween RA/NRA participants which meant there was also no improvement over the year in RA bone quality.Conclusions: Early changes in peri-articular bone density and microstructure seen in RA are consistent withchanges more commonly seen in aging bone and are slow or resistant to recover despite well controlledinflammatory joint symptoms with early DMARD therapy.Keywords: High resolution – Peripheral quantitative computed tomography (HR-pQCT), Early rheumatoid arthritis,Disease modifying Antirheumatic drugs, Bone health, Osteoporosis, Fracture risk* Correspondence: Lynne.Feehan@gmail.com1Department of Physical Therapy, University of British Columbia, Vancouver,BC, Canada2Arthritis Research Canada, 5591 No. 3 Road, Richmond, BC V6X 2C7, CanadaFull list of author information is available at the end of the article© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link tothe Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Feehan et al. BMC Musculoskeletal Disorders  (2017) 18:521 DOI 10.1186/s12891-017-1888-3BackgroundRheumatoid arthritis (RA) affects 1% of adults, mostcommonly in women (3:1) aged 40 to 70 years [1].Despite marked improvement in the clinical manage-ment of progressive joint disease, individuals with RAcontinue to live with underlying bone changes and aretwice as likely to sustain any fracture compared topeople without RA [2–6]. The underlying mechanism(s)for changes in bone health in RA are likely multi-factorial. These may include: 1) response to local inflam-matory cytokines, hypervascularity or bone edema in theperiarticular bone adjacent to inflamed joints [7], 2)systemic inflammatory mediated catabolic imbalance innormal bone homeostatic mechanisms [8], 3) bone adap-tive resorption in response to physical inactivity [9, 10],and 4) effect of RA medications [11–13].Clinically, radiographic (x-ray) progression of periarticu-lar osteopenia, joint space narrowing and focal bony ero-sions, primarily in the hand and wrist, are considered thehallmark of poor disease control [14]. Magnetic resonanceimaging, computed tomography, dual x-ray absorpti-ometry and digital x-ray radiogrammetry can also identifymacro structural bone changes in RA [15–17]. However,these clinical imaging technologies are unable to evaluatemicro structural adaptations that accompany bone andjoint diseases. High Resolution – peripheral QuantitativeCT (HR-pQCT) is a reliable and precise imaging systemthat detects and quantifies micro-structural bone alter-ations, and can do so before macro-structural changesappear [18]. Specifically, standardized protocols for HR-pQCT image acquisition and evaluation methods in RApermit characterization of periarticular trabecular andcortical bone volumetric density and microstructure inthe periarticular regions of the metacarpal head (MH2,3)and distal radius (UUD - ultra-ultra-distal) [19, 20].To date, only a small number of cross-sectional HR-pQCT studies evaluated periarticular bone quality inthose with RA [21–27]. Notably, there was consistentevidence of changes in periarticular bone density andmicrostructure in the Metacarpal Head (MH) or DistalRadius in individuals living with RA for 8 or more years,[21–26], as well as, emerging evidence of early bonechanges potentially occurring before the onset of inflam-matory joint symptoms [27]. However, given the cross-sectional design and heterogeneity of RA participants inthese previous studies it was not possible to define whenchanges in bone micro-structure occurred in relation toRA onset or response to RA treatments.We aimed to fill this gap by examining periarticularbone density and microstructure adaptations in patientswith early RA who receive care consistent with currentclinical guidelines [28–30]. Specifically, the purpose of thisstudy was to use HR-pQCT to examine: 1) differences intrabecular and cortical bone density and microstructure inMH and DR periarticular bone in individuals with earlyRA (< 1 year) and started on Disease Modifying Antirheu-matic Drug (DMARD) therapy at the time of diagnosis,and 2) whether bone density and microstructure changesimprove, persist or deteriorate over 12-months. We hy-pothesized that we would identify early microstructuraldamage within a year of RA diagnosis and that earlymicro-structural bone damage would persist (not improveor worsen) despite adequate disease control with first lineDMARD [+/- Glucocorticoid (GC)] therapies over thesubsequent 12-months.MethodsWe conducted a one-year, prospective observationalcohort study in individuals living independently in thecommunity in a large urban metropolitan region(Greater Vancouver Regional District, British Columbia,Canada). All participants were 19 years or older and pro-vided informed consent. RA participants had to betreated by a rheumatologist and have a rheumatologist-confirmed diagnosis of new onset RA (< 1 year) basedon the American College of Rheumatology / EuropeanLeague Against Rheumatism (ACR/EULAR) 2010criteria [31]. Individuals were excluded if they had anyhealth condition that prevented participation, had metalor surgical implants in their dominant arm, were preg-nant, had sustained a fracture in their dominant arm inthe previous 12 months, or were unable to provide con-sent. Non-RA (NRA) participants were also excluded ifthey had been told by a physician they had any inflam-matory joint disease or rheumatologic condition.Patients diagnosed with new onset RA were identifiedfrom nine rheumatology clinics and the research teamconfirmed eligibility. For comparison, sex and age-matched NRA participants were recruited through wordof mouth, flyer postings in health care settings, email re-quests and research website postings. NRA participantswere screened for eligibility and were matched with anRA study partner by sex and age within 2 years.EvaluationsParticipants attended baseline and 12-month in-personevaluations. Physical Evaluations: Measures of height(cm) and weight (kg) [Body Mass Index (BMI): Kg / m2]were collected for all participants and a 28-joint active(Tender and Swollen) joint count for RA participants[32]. Self-Reported Measures: Participants completed aGeneral Health and Lifestyle questionnaire. RA partici-pants also completed a Stanford Health AssessmentQuestionnaire - Modified (mHAQ) [33]. HR-pQCTImaging: The imaging protocol has been described indetail elsewhere [19]. Briefly, we acquired HR-pQCTimages with a Scanco XtremeCT imaging system[Scanco Medical AG, Switzerland] using standardFeehan et al. BMC Musculoskeletal Disorders  (2017) 18:521 Page 2 of 13manufacturer recommended parameters [19]. For the ra-dius, the reference line was the medial/distal radius(Fig. 1a – Scout View). The scan started 3 mm proximalto this reference line and extended 9.02 mm (110 slices)proximally (Fig. 1a – Scout View). For the metacarpalhead the reference line was the tip of the most distalsecond or third metacarpal head. The scan started 4 mmdistal to this reference line and extended 18.04 mm (220slices) proximally [19, 20]. (Fig. 1a -Scout View). Each110-slice scan takes 2.8 min with an effective dosage ofless than 2 μSv [19].Medical record/medication dataAt baseline an internal medicine resident extractedinformation from rheumatologists’ electronic medicalrecords including; RA diagnosis date, timing and type ofprescribed RA medication(s), and RA blood markers[anti-citrullinated peptide autoantibodies (ACPA) and/orRheumatoid Factor (RF) Positive] at time of diagnosis.At 12-months, RA participants completed a log of RAmedications prescribed and taken in the previous6 months. The cumulative dosage of any DMARD orGC medications were not collected at either time point.HR-pQCT image analysesOne of three trained operators [intra-rater reliability, 10scans measured twice, Pearson’s r > 0.9] analyzed all im-ages using manufacturer’s evaluation software (SCANCO,V 6.0) [19]. Prior to analysis, each image was graded formotion artifact using a 5-point grading scale and only im-ages rated 3 or higher were used [19]. Regions of Interestincluded the ultra-ultra-distal radius (UUD: 110 slices,starting 3 mm proximal to radius reference line and run-ning proximally), metacarpal head two (MH2: 110 slicesstarting at the distal tip of MH2 running proximally), andmetacarpal head three (MH3: 110 slices starting at the dis-tal tip of MH3 running proximally) (Fig. 1a – Scout View)[19]. We ran standard manufacturer and direct transform-ation image analyses scripts to segment the cortical andtrabecular bone regions and measure bone density andmicrostructure (Fig. 1b, c – Cortical/Trabecular Compart-ment Segmentation) [19].Density measures included apparent bone mineral density(BMD - mgHA/cm3) for cortical and trabecular boneregions, and cortical bone material bone density (TMD -mgHA/cm3). Measures of cortical microstructure included:thickness (CtTh - mm), thickness variability CtThSd - mm),volume fraction (BV/TVcort - %) and porosity (CtPo - %).Measures of trabecular microstructure included: volumefraction (BV/TVtrab - %), number (TbN – 1/mm), thickness(TbTh - mm), separation (TbSp - mm), separation variability(TbSpSd - mm), connective density (TbCD - mm4) andstructural model index (SMI 0–3; lower values indicate moreplate-like verses more rod-like structure) [19].Statistical analysesWe examined differences in baseline anthropometrics(Age, Sex, BMI) and Fracture Risk between RA andFig. 1 a 150 mm Scout View Image. Dots = Reference points for the distal radial (medial distal cortex radius) and metacarpal head (distal tip ofmost proximal MH) scans. Larger shaded boxes = Distal Radius (110 slices) and Metacarpal (220 slices) scan lengths. Smaller boxes with UUD, MH2and MH3 text = Three Regions of Interests (ROIs) evaluated (UUD = Ultra-ultra distal, MH =Metacarpal head 2 or 3). b Single HR-pQCT image slicesof a cross-sectional image of MH (Top) and Distal Radius (Bottom) scans. Lines show cortical bone periosteal and endosteal semi-automaticsegmentation. c 3-Dimensional reconstructed images of MH (top) and UUD (bottom) scans of a non-RA participant, with the cortical bone andtrabecular bone regions separately reconstructedFeehan et al. BMC Musculoskeletal Disorders  (2017) 18:521 Page 3 of 13NRA participants using Paired Student T-tests (twotailed, p < 0.05). For the longitudinal analyses of micro-structural bone quality, we conducted a General LinearModelling 2 × 2 repeated measures analyses for the HR-pQCT image analyses. We compared disease status (RAvs NRA) over Time [Baseline vs 12 Month] using a two-tailed analysis with a Sidak multiple comparison adjust-ment. We set alpha at p = 0.05. We examined maineffects for disease (RA vs NRA, independent of time),time (change over 1-year, independent of disease status)and interaction [disease (RA vs NRA) x time (baseline vs12- months)]. We did not correct for separate statisticalanalyses for multiple HR-pQCT imaging outcomes. Allstatistical analyses were completed using SPSS softwarev. 23 (IBM Corp, Armonk, NY).ResultsRecruitment/retentionForty-nine individuals diagnosed with RA in the previ-ous year by one of nine rheumatologists were screenedfor eligibility, with 19 excluded (39% excluded). Reasonsfor exclusion were RA diagnosis at the time of screeninggreater than 1 year (n = 10), not able to commit to study(n = 6), or language barrier (n = 3). Of 43 NRA individ-uals screened eight were excluded (19% excluded)because they were unable to commit to the study (n = 5)or they reported a co-morbid inflammatory health con-dition (n = 3). Of the 35 eligible NRA participants fivewere ultimately excluded as they were not matched withan RA study partner. The 60 participants were seriallyrecruited to the study and evaluated at baseline over an11-month time period. Fifty-six participants (26 RA/30NRA) completed the 12-month evaluation (93% comple-tion); 54 were evaluated at 52-weeks (+/− 4 weeks) and2 were evaluated at 60 weeks. Four RA participantswithdrew [1 death, 2 serious illness (cancer, cardiac dis-ease), 1 no longer interested] and their 4 sex/age-matched NRA partners were excluded from the finallongitudinal analyses. Five images were excluded fromanalyses due to motion artifact at baseline (4.2%; 2-MH,3-UUD) and at 12-months (9.6%; 4-MH, 1-UUD). Ofthe 26 matched pairs of participants at 12 months (n =52); 23 pairs (88.5%; n = 46) had baseline and 12-monthUUD images and 22 pairs (84.6%; n = 44) had baselineand 12-month MH images for comparison.Participant demographicsSee Table 1 for further details of participant demograph-ics at baseline. In summary, of the 60 participants, 48were females with a mean age of 53 years varying from21 to 74 years. The RA and NRA pairs were wellmatched by age and sex, with exact matching for sexand no statistically significant difference in age, with theRA participants on average 53 years old, compared tothe NRA participants 52 years old. On average, femaleRA and both RA and NRA males were overweight (BMI:25–29.9 kg/m2), whereas, NRA females were of highnormal body weight (BMI 24.8 kg/m2). [34] The meanBMI was significantly higher in the RA group forwomen, but not for men. The mean Fracture Risk As-sessment Tool (FRAX®Canada) 10-year major fracture andhip fractures risk scores were both significantly higheramong participants with RA [35]. Some other differencesat baseline included, 6 RA participants smoked com-pared to 1 NRA participant, 7 RA participants comparedto 1 NRA participant had been told they may have poorbone health (i.e. osteopenia or osteoporosis) and 3 indi-viduals with RA reported taking a bone antiresorptive oranabolic medication in the last 5 years [36]. As well, 19RA participants reported taking calcium or vitamin Dnutritional supplements compared with 13 of NRAparticipants.RA participant disease characteristicsSee Table 2 for further details of RA participant charac-teristics. In summary, at baseline the 30 RA participantswere on average 7.7 months (varying from 1 to15 months) since diagnosis. Notably, one RA participantwas scanned at 15-months post diagnosis which was aprotocol violation. This occurred as the participant didattend the baseline evaluation at 12-months post diagno-sis, however, they could not complete the evaluation dueto physical illness. Unfortunately, the re-evaluation wassubsequently delayed due to a 3-month planned vac-ation. Twenty-two of the RA participants were ACPAand/or RF positive at the time of diagnosis. At baseline,29 of 30 RA participants received one or more non-biologic DMARD, including Methotrexate, Hydroxy-chloroquine, or Sulfasalazine. Of these, 14 receivedsingle, 7 received double and 8 received triple DMARDtherapy. Thirteen individuals received only DMARDtherapy, 15 received DMARDs in combination with oralglucocorticoid (at least one episode of Prednisone, >5 mg/day, > 3 weeks), 1 received DMARD in combin-ation with an anti-TNF (Tumor Necrosis Factor) bio-logic medication (Adalimumab) started 8-months postdiagnosis and 1-week prior to baseline imaging and 1person having only received glucocorticoid medication.DMARD therapies were started on average 0.1 monthafter diagnosis, whereas, oral glucocorticoid (GC) medi-cation was initiated on average 1.8 months prior to finalRA diagnosis. The negative value for onset of GC medi-cation can be explained in part by a typical 4 to 6-weektime interval between the initial visit to the rheumatolo-gist and final diagnosis of RA, when GC medications areoften started prior to definitive RA diagnosis. Addition-ally, one participant had received a GC medication pre-scription (> 5 mg/day for 3 weeks) from their primaryFeehan et al. BMC Musculoskeletal Disorders  (2017) 18:521 Page 4 of 13care physician 11-months prior to the referral to arheumatologist. At 12-months, 24 of 26 RA participantswere still receiving DMARD therapy. However, only 2had taken any oral glucocorticoid medications in com-bination with DMARDs in the previous 6 months and19 had tapered down to single DMARDs therapy.Whereas, one person was taking only an anti-TNFbiologic medication (Adalimumab), while another hadopted out of taking all prescribed RA medications as apersonal choice.RA participant clinical characteristicsSee Table 2 for further details of RA participant clinicalcharacteristics. This study used a 28-joint active countas a measure for evidence of active joint inflammation(i.e. no or some active joints) at the time of imaging,with active inflammation of any joint defined as bothswollen and tender. At baseline, 9 of 30 RA participantspresented with no active joints. Of the remaining 21 RAparticipants with at least one active joint, the medianactive joint count was 4. At 12-months, 15 of 26 RAparticipants presented with no active joints. Of theremaining 11 participants with at least one active joint,the median active joint count was 1. At baseline RA par-ticipants reported low levels of functional disability[DI1–3: Mean 0.59 (+/−0.60)], pain (VAS0–100: Mean 21.2(+/− 16.4) and impact on well-being [VAS0–100: Mean23.7 (+/− 18.8)] [33]. Notably, RA participants alsoreported minimal improvement in their self-reportedfunctional disability, pain or impact on well-being over1-year [37].HR-pQCT imaging – Disease (RA vs NRA) effectsSee Table 3 for details of the values and results of thelongitudinal statistical analyses for the HR-pQCT diseasemain effect, representing the overall differences betweenRA and NRA participants independent of time at allthree sites. In summary, differences in density included:RA participants had significantly lower trabecular bonedensity at all three sites (varying from 15.4 to 10.9%lower), significantly lower cortical bone apparent densityat both MH sites (MH2 8.7% and MH3 9.9% lower) andsignificantly lower cortical bone material density at theMH2 site (MH2 3.9% lower). Differences in cortical bonemicro-structure included: At the UUD site RA partici-pants demonstrated significantly greater variability incortical thickness (9.3% greater variability in thickness)and significantly less cortical bone volume at both MHsites (MH3: 3.8% MH2: 4.5% lower). Trabecular bonemicro-structure differences included: At all three sitesRA participants had significantly larger and more vari-able sized spaces between trabeculae (varying from11.9% to 16.0% larger spaces and 22.9% to 35.2% morevariable sized spaces). At all three sites RA participantstrabecular matrix was also significantly more rod- versesplate-like shaped trabecular matrix (SMI varied from20.8% to 84.1% greater) with significantly lower trabecu-lar bone volume (varying from 12 to 8% lower). At theUUD and MH2 sites, RA participants also had signifi-cantly fewer trabeculae (UUD 7.2% lower; MH2 9.0%lower). Whereas, at the UUD site RA participants alsohad trabecular that were less connected (13.0% lesstrabecular connectivity). Figure 2 shows plots (mean +/−SEM) for selected density and microstructural variablesTable 1 Baseline Demographics: Rheumatoid Arthritis vs Non-Rheumatoid Arthritis Participants (n = 60)Domain Parameter RA (n = 30) NON-RA (n = 30)Age Age in Years [mean (SD), min-max] 53.3 (13.7), 21–74 51.6 (13.6), 23–70Sex Sex [# (%) - Male, Female] 6 (20%), 24 (80%) 6 (20%), 24 (80%)Body Mass Index (BMI) BMI Female [mean (SD), min-max] 28.3 (7.9), 16.8–49.3 24.3 (4.8), 18.9–37.7BMI Male [mean (SD), min-max] 27.5 (4.1), 20.1–32.5 26.8 (2.5), 24.1–29.9Fracture Risk – FRAX ® [35] 10 year - Major Fracture Probability (%) - FRAX (Canada),no aBMD [mean (SD), min-max]11.2 (9.9), 1–43 5.9 (4.9), 1–1810 year - Hip Fracture Probability (%) - FRAX (Canada),no aBMD [mean (SD), min-max]3.2 (4.2), 0–17 1.0 (1.3), 0.1–5.5Bone Health - Risk Factors(Self-Report)Current Smoker [# (%)] 6 (20%) 1 (3%)*Current Alcohol (0 to 4, higher score more alcoholconsumption) [median, mode (%)]1, 1 (30%) 2, 1 (37%)Told in the last five years by any physician that they(may) have osteoporosis [# (%)]7 (23%) 1 (3%)Bone Health - Medications/NutritionalSupplements(Self-Report)Bone Antiresorptive or Anabolic Medication -Last 5 years [#, (%)]3 (10%) 0 (0%)Current Calcium, Vitamin D Supplement Intake [#, (%)] 19 (63%) 13 (43%)*Current Alcohol Use (alcohol drinks / week): ‘0’ none, ‘1’ <1, ‘2’ 1 to 3, ‘3’ 4 to 7, ‘4’ >7aBMD = Apparent Bone Mineral Density measured by DXABold indicates a statistically significant difference between RA and NRA participants (Two tailed, Paired Student T-test)Feehan et al. BMC Musculoskeletal Disorders  (2017) 18:521 Page 5 of 13with consistent differences between RA and NRA partic-ipants across the three ROIs examined in this study, aswell as, notable differences in the density and micro-structure values of the two MH head ROIs and the UUDROI. To illustrate further the differences between RAand NRA participants, Fig. 3 shows the typical visualdifferences in trabecular bone micro-structure seen in 3-Dimensional reconstructed images of the UUD and MHsites in age- and sex-matched RA and NRA studypartners.HR-pQCT imaging - time effectsSee Table 4 (Additional file 1) for details of the datavalues and results of the statistical analyses for the longi-tudinal time main effect analysis, representing the agingeffect over 12-months for all participants independent ofdisease status. In summary, density changes over timeincluded: Cortical bone material density at the MH3 siteand UUD trabecular bone apparent density site weresignificantly reduced over 12-months (MH3 0.6% lower,UUD 2.5% lower). Changes in cortical bone micro-structure over12-months included: UUD cortical thicknessand porosity significantly increased over 12-months(Thickness 4.7% greater; Porosity: 29.6% greater).Trabecular bone micro-structure changes over 12-monthsincluded: At the UUD site, trabecular number, connectivityand SMI all increased significantly across one year (Num-ber: 1.9% greater, Connectivity 2.7% greater and SMI 3.4%greater). Whereas, trabecular thickness, trabecular spacingand variability were significantly lower (Thickness: 1%Table 2 Rheumatoid Arthritis (RA) Participant Clinical CharacteristicsDomain Parameter RA Baseline(n = 30)RA 12-Months(n = 26)RA Diseases Duration Months Since Diagnosis by a Rheumatologist[mean (SD), min-max]7.7 (4.9), 1–15* Baseline OnlyRheumatoid Arthritis Blood Markers Anti-cyclic citrullinated protein antibodies(anti-CCP) and/or Rheumatoid Factor (RF) Positive[# (%)]22 (73%) Baseline OnlyRA Medication Combinations **8 DMARD Only [# (%)] 13 (43%) 22 (85%)DMARD + Glucocorticoid [# (%)] 15 (50%) 2 (7%)DMARD + Biologic [# (%)] 1 (3%) 0 (0%)DMARD + Glucocorticoid + Biologic [# (%)] 0 (0%) 0 (0%)Single DMARD [# (%)] 14 (47%) 19 (73%)Double DMARD [# (%)] 7 (23%) 4 (15%)Triple DMARD [# (%)] 8 (27%) 1 (4%)*** Glucocorticoids Only [# (%)] 1 (3%) 0 (0%)**** Biologic Only [# (%)] 0 (0%) 1 (4%)***** No RA medications [# (%)] 0 (0%) 1 (4%)RA Medication Timing Months to any DMARD once Diagnosed (n = 29)[mean (SD), min-max]0.1 (1), −4 to 3 Baseline OnlyMonths to Glucocorticoids Once Diagnosed (n = 16)[mean (SD), min-max]−1.8 (3), −11 to 1 Baseline OnlyMonths to Biologic Once Diagnosed (n = 1) 8 Baseline OnlyPhysical Evaluation – 28-Joint Active(Tender AND Swollen) Joint CountNumber participants with NO Tender AND Swollen Joints [n (%)] 9 (30.0) 15 (57.7)Number participants with at least one Tender AND Swollen Joint[n (%)]21 (70.0) 11 (42.3)Number of Tender AND Swollen Joints [mean (SD), min-max] 4.2 (2.3), 1–9 3.6 (3.0), 1–9Stanford Health AssessmentQuestionnaire- Modified (MHAQ) [33]Disability Index - 0 to 3 [mean (SD), min-max] 0.59 (0.60), 0 to 2.13 0.48 (0.66), 0 to 2.00Pain Visual Analog Scale (VAS) - 0 to 100 [mean (SD), min-max] 21.2 (16.4), 0 to 65 20.4 (23.3), 0 to 89Global Functioning VAS - 0 to 100 [mean (SD), min-max] 23.7 (18.8), 1 to 68 18.2 (21.7), 1 to 88*One RA participant received baseline HR-pQCT scan at 15-months post-diagnosis. The participant attended the baseline evaluation at 12-months post diagnosis,but was sick and could not be re-scheduled due to a planned 3-month vacation**Non-Biologic Disease-Modifying Anti-Rheumatic Drug (DMARD): Methotrexate, Hydroxychloroquine, Sulfasalazine***Glucocorticoid (GC): > = 5 mg / day for ≥3 weeks****Biologic anti-TNF: Adalimumab*****One person moved to an alternative medicine practitioner and stopped all RA prescribed medsNOTE: Cumulative dosage for any RA medications and medication adherence were was not trackedFeehan et al. BMC Musculoskeletal Disorders  (2017) 18:521 Page 6 of 13Table3HR-pQCTDisease(RheumatoidArthritisvsNoRheumatoidArthritis)MainEffectsSummaryRegionofInterest(ROI)ParameterOutcomeVariableRAParticipantsNRAParticipantsPValueGroupDiffValue(%)MeanSEMMeanSEM(2-tailed)(RA-NRA)UUD(n=46,23pairs)VolumetricBoneDensityCorticalMaterialBoneMineralDensity(mgHA/cm3 )TMDcort946.548.61945.367.670.9031.19(0.1%)CorticalApparentBoneMineralDensity(mgHA/cm3 )BMDcort779.7115.64782.1414.980.889−2.43(−0.3%)TrabecularApparentBoneMineralDensity(mgHA/cm3 )BMDtrab159.846.99188.157.190.001−28.31(−15.0%)CorticalMicrostructureCorticalThickness(mm)-DirectCtTh0.730.030.690.030.2410.05(6.7%)CorticalThickness_SD(mm)CtThSd0.300.010.270.010.0470.03(9.3%)CorticalBoneVolumeFraction(%)BV/TV cort91.55%0.76%91.56%0.98%0.993−0.01(0.0%)CorticalPorosity(%)CtPo1.76%0.22%1.71%0.24%0.8300.04(2.6%)TrabecularMicrostructureTrabecularBoneVolumeFraction(%)-DirectBV/TV trab26.08%0.92%29.66%0.88%0.001−3.57(−12.1%)TrabecularConnectiveDensity(mm4 )TbCD4.140.224.760.200.005−0.62(−13.0%)TrabecularStructuralModelIndex(0–3)SMI1.940.081.610.080.0020.33(20.8%)TrabecularNumber(1/mm)TbN1.910.062.060.050.016−0.15(−7.2%)TrabecularThickness(mm)-DirectTbNSd0.1950.0020.1990.0020.130−0.005(−2.3%)TrabecularThickness_SD(mm)TbTh0.070.000.070.000.4190.001(1.9%)TrabecularSeparation(mm)TbSp0.520.020.460.010.0060.05(11.9%)TrabecularSeparation_SD(mm)TbSpSd0.220.020.180.010.0230.04(22.9%)MH3(n=44,22pairs)VolumetricBoneDensityCorticalMaterialBoneMineralDensity(mgHA/cm3 )TMDcort815.1710.67840.609.700.055−25.43(−3.0%)CorticalApparentBoneMineralDensity(mgHA/cm3 )BMDcort537.7715.52589.1216.170.012−51.35(−8.7%)TrabecularApparentBoneMineralDensity(mgHA/cm3 )BMDtrab234.048.13262.577.890.004−28.53(−10.9%)CorticalMicrostructureCorticalThickness(mm)-DirectCtTh0.350.020.390.020.107−0.04(−9.2%)CorticalThickness_SD(mm)CtThSd0.220.020.240.020.285−0.03(−11.1%)CorticalBoneVolumeFraction(%)BV/TV cort78.70%1.11%81.79%1.11%0.020−3.09(−3.8%)CorticalPorosity(%)CtPo0.92%0.07%1.04%0.07%0.2840.12(−11.2%)TrabecularMicrostructureTrabecularBoneVolumeFraction(%)-DirectBV/TV trab35.03%0.90%38.14%0.74%0.002−3.10(−8.1%)TrabecularConnectiveDensity(mm4 )TbCD6.450.327.050.370.210−0.61(−8.6%)TrabecularStructuralModelIndex(0–3)SMI0.950.100.580.100.0050.37(63.5%)TrabecularNumber(1/mm)TbN2.180.072.340.050.0510.16(−6.9%)TrabecularThickness(mm)-DirectTbNSd0.2060.0030.2080.0030.651-0.002(−0.8%)TrabecularThickness_SD(mm)TbTh0.070.000.070.000.1820.002(3.4%)TrabecularSeparation(mm)-DirectTbSp0.440.020.390.010.0110.05(12.6%)TrabecularSeparation_SD(mm)-DirectTbSpSd0.240.020.180.010.0120.06(32.7%)Feehan et al. BMC Musculoskeletal Disorders  (2017) 18:521 Page 7 of 13Table3HR-pQCTDisease(RheumatoidArthritisvsNoRheumatoidArthritis)MainEffectsSummary(Continued)RegionofInterest(ROI)ParameterOutcomeVariableRAParticipantsNRAParticipantsPValueGroupDiffValue(%)MeanSEMMeanSEM(2-tailed)(RA-NRA)MH2(n=44,22pairs)VolumetricBoneDensityCorticalMaterialBoneMineralDensity(mgHA/cm3 )TMDcort800.409.53832.978.520.003−32.57(−3.9%)CorticalApparentBoneMineralDensity(mgHA/cm3 )BMDcort547.0714.90607.4616.580.002−60.39(−9.9%)TrabecularApparentBoneMineralDensity(mgHA/cm3 )BMDtrab227.138.17268.499.010.000−41.37(−15.4%)CorticalMicrostructureCorticalThickness(mm)-DirectCtTh0.350.010.380.010.090−0.03(−7.4%)CorticalThickness_SD(mm)CtThSd0.200.010.190.010.9370.001(0.6%)CorticalBoneVolumeFraction(%)BV/TV cort80.03%1.21%83.77%1.26%0.016−3.74(−4.5%)CorticalPorosity(%)CtPo0.92%0.06%0.96%0.06%0.626−0.04(−4.3%)TrabecularMicrostructureTrabecularBoneVolumeFraction(%)BV/TV trab33.69%0.91%38.17%0.87%0.0002–4.48(11.7%)TrabecularConnectiveDensity(mm4 )TbCD6.240.286.940.330.117−0.70(−10.1%)TrabecularStructuralModelIndex(0–3)SMI1.060.100.580.100.00010.48(84.1%)TrabecularNumber(1/mm)TbN2.080.072.280.060.014−0.20(−9.0%)TrabecularThickness(mm)-DirectTbNSd0.2030.0030.2100.0040.090−0.01(−3.5%)TrabecularThickness_SD(mm)TbTh0.070.000.070.000.445−0.003(−3.9%)TrabecularSeparation(mm)TbSp0.470.020.400.010.0060.06(16.0%)TrabecularSeparation_SD(mm)TbSpSd0.270.020.200.020.0080.07(35.2%)BOLD:P<0.05;Italics:p≤0.10NOTE:NoadjustmentformultipleindependentstatisticalanalysesofHR-pQCToutcomesFeehan et al. BMC Musculoskeletal Disorders  (2017) 18:521 Page 8 of 13lower, Spacing 1.7% lower and variability 1.8% lower).Additionally, at the MH3 site, trabecular bone volume,thickness and thickness variation all increased significantly(volume 0.9% higher, thickness 0.7% higher and thicknessvariation 1.8% higher).HR-pQCT imaging - interaction (disease x time) effectsSee Table 5 (Additional file 1) for full details of the datavalues and results of statistical analyses for the RA vsNRA by Baseline vs 12-months (interaction) main effectanalyses. There was no significant interaction maineffects for any cortical or trabecular bone density ormicrostructure outcomes examined, which indicates thatthe rate of change over 12-months was not different forthe RA and NRA participants. Or alternately, that theRA participants did not show either an increased ordecreased rate of change in bone micro-structure overthe 12-months relative to the NRA participants, indicat-ing as well that any underlying difference in bone micro-structure at baseline in the RA participants relative tothe NRA participants persisted over the 12-months.DiscussionDespite marked improvements in early management ofinflammatory joint symptoms, individuals living with RAcontinue to live with poor bone health and increasedfracture risk compared to peers [2–6]. Our study is thefirst to explore prospective changes over 1-year in bonedensity and microstructure at the MH and DR in indi-viduals recently diagnosed with RA who have beentreated by a rheumatologist with care consistent withcurrent practice guidelines. As we hypothesized, despitethe introduction of DMARD (+/- oral glucocorticoids)medications at time of diagnosis, individuals living withearly RA in this study demonstrated marked differences inperiarticular trabecular and cortical bone density andmicrostructure, compared with NRA counterparts. More-over, the pattern of very early micro-structural bonechanges seen in those with newly diagnoses RA werea bc de fFig. 2 Common Changes in Density and Micro-structure across Regions of Interest: Bar graphs [mean (SEM)] showing differences betweenrheumatoid arthritis (RA) and Non-RA (NRA) participants for selected density and microstructural variables with consistent differences across twoor three of the regions of interest examined in this study. This figure also illustrates regional differences density and microstructural in the twoMH compared to the UUD ROIsFeehan et al. BMC Musculoskeletal Disorders  (2017) 18:521 Page 9 of 13consistent with changes more commonly seen in agingbone. After one year, the degree of detectable changes inperiarticular density and microstructure that would nor-mally occur with 1-year of aging, did not differ betweenindividuals living with and without early RA. This speaksto early control of the disease activity with first lineDMARD medication therapy (+/− glucocorticoids) thatseemingly also mitigated any increased rate of systemic in-flammatory mediated bone turnover, as the bone damagein RA did not worsen compared to NRA participants over12-months. However, and again as we hypothesized, therewas also no evidence of improvement in periarticulardensity or microstructure in the RA group. This suggeststhat the microstructural bone damage identified withinthe first year of diagnosis in the RA participants was re-sistant or very slow to recover despite achieving andmaintaining relatively low levels of active joint inflamma-tion and minimal self-reported functional limitation withthe use of non-biologic DMARD therapy (+/- Gluco-corticoid use).Differences in periarticular bone density and microstruc-ture seen in the first year following an RA diagnosis arenotably consistent with changes in bone more commonlyseen with aging in post-menopausal women and olderadults of both sexes. As we age the homeostatic balance inbone remodeling in adulthood shifts to a negative imbal-ance, where bone is resorbed at a greater rate than it is re-placed [38]. With aging, the pattern of bone loss in thecortical bone and trabecular bone regions is predictable.These changes include increased bone resorption at theendocortical bone surface leading to thinner and morevariable thickness in the cortical shell. Cortical bone alsobecomes more porous and less materially dense [39, 40].Trabeculae become thinner, more variable in thickness andbecome less connected resulting in more ‘rod-like’compared with ‘plate-like’ structure as observed in youngerbone [41]. These changes in the trabecular bone matrixalso results in larger and greater variability in size of spacesbetween trabeculae [42]. Together, these age-relatedchanges in cortical and trabecular bone microstructureultimately results in a structurally weaker bone [43]. More-over, that the age-related changes in cortical and trabecularbone microstructure reported in the literature are mark-edly similar to the pattern of cortical and trabecular bonechanges we identified within the first year following an RAdiagnosis. However, and importantly, that these apparentFig. 3 Examples of cross-sectional reconstructions from UUD radius scans (distal view - left column) from two 47-year-old women who were RAand NRA matched study partners and MH3 scans (proximal view – right column) from two 22-year-old women who were RA and NRA matchedstudy partners. The reconstructed images in the top row are from the RA participants and the reconstructed images in the bottom row are fromthe NRA participants. Images illustrate marked visual differences in trabecular bone microstructure between the RA and NRA participants. The 3-Dreconstructions show the peripheral cortical region in lighter shading compared to the central trabecular region (darker shading)Feehan et al. BMC Musculoskeletal Disorders  (2017) 18:521 Page 10 of 13bone-aging changes were evident in both sexes and acrossall ages of RA participants. Suggesting that patterns ofbone changes in early RA may be similar to the systemichormonal mediated catabolic (negative) remodeling inbone commonly seen with aging, with the negative imbal-ance in bone remodeling in RA likely mediated more byproinflammatory cytokines that are known to be osteoclas-togenic in nature, such as RANKL and Osteoprotegerin(OPG) [8, 44, 45].Marked changes in bone microstructure a few monthsafter a RA diagnosis implies that changes may have oc-curred rapidly at or around the time of inflammatoryjoint symptom onset and prior to response to RA medi-cations. These changes may also have occurred over alonger period of time prior to onset of inflammatoryjoint symptoms. RA participants in our study were notimaged at the time of, or prior to the diagnosis. Thus,we are not able to discern which of these time-relatedfactors have contributed to the early underlying changesin bone microstructure. However, as previously reportedby Kleyer et al. (2013), individuals who are ACPA posi-tive with no systemic inflammatory joint symptoms canshow evidence of reduced cortical bone density andthinner and more porous cortices in the MH [27].Our findings are largely consistent with previouscross-sectional studies exploring microstructural bonechanges in individuals living with RA of longer durationcompared to age and sex matched controls [18, 21–26].Fouque-Aubert et al. (2010) [21], first reported lowertrabecular bone density and trabecular thickness in theMH region in participants with an RA disease durationaverage of 9 years, as well as, lower trabecular thicknessin the MH if a subgroup of early RA participants [Mean(SD) years: 1.0 (0.5)]. Subsequent cross-sectional studieshave also examined HR-pQCT differences in periarticu-lar bone in individuals living with RA for 8 or moreyears compared to controls and all have reported notabledifferences in bone density and microstructure in theMH or DR [18, 21–26]. Our study provides additionalevidence of reduced bone density and altered corticaland trabecular bone microstructure in the periarticularMH and DR (UUD) regions in individuals with recentlydiagnosed RA that are consistent with age-related bonechanges. Consistent periarticular micro-structural bonedamage across all three regions of interest examined inour study also provides further indication that the peri-articular bone changes associated with early RA arelikely systemically mediated to some degree. Further-more, our findings indicate that worsened periarticularbone microstructure detected within a few months ofinflammatory joint symptom onset persisted over 1-yeardespite early and clinically effective management ofacute inflammatory joint symptoms with DMARD ther-apy, which may be a contributing factor to the persistentfracture risk in individuals living with RA despite moreeffective care with DMARD therapies [2–6].Our study has several limitations. The first is the smallsize of the cohort, which may not represent the broaderspectrum of individuals with RA in terms of severity ofearly symptoms or responsiveness to first line DMARDmedications. In addition, the small cohort may have af-fected our ability to identify differences that may haveexisted due to lack of power related to large variabilityin some of the HR-pQCT outcomes evaluated. RAparticipants also received care from a small number ofrheumatologist practicing in one large urban metropol-itan region within Canada. Clinical care practices ofthese rheumatologists may not reflect practice patternsof other rheumatologists who provide care in othergeographic regions or other health care systems or forindividuals with limited access to timely specialist care[46–49]. We also only monitored change in bone micro-structure over 1-year, which may have limited our abilityto detect slower age-related changes. HR-pQCT hasexcellent precision (CV% varying from <1 to 3%) and isable to detect annual changes in many aspects of bonemicrostructure [19, 39, 42]. However, we may haveneeded a longer timeframe to identify measurablechange in some aspects of bone quality, particularlychanges in cortical bone density and microstructuregiven the greater imprecision with the evaluation ofsome aspects of cortical bone density and microstruc-ture [19, 49]. We also did not use image analysestechniques to evaluate joint space or presence of peri-articular erosions [18]. Nor did we utilize alternatemethods for cortical bone segmentation and measure-ment of cortical porosity [50]. These HR-pQCT imageevaluation approaches may have identified differences inperiarticular bone and joint health in our participantsthat we were unable to detect with our methods. Finally,we did not examine the association between changes inbone quality and RA clinical factors, as this study wasnot designed or powered to secondarily explore thestrength or direction of a potential relationship betweenRA disease factors (i.e. disease activity or ACPA status)or RA medications (i.e. DMARD only vs DMARD incombination with GC) and changes in microstructuralbone quality. This would be an important avenue forfuture research considerations.ConclusionsDisadvantageous changes in trabecular and cortical bonedensity and microstructure occurs early in RA and areconsistent with accelerated changes more commonly seenwith aging bone. Moreover, these early changes in bonemicrostructure appear resistant or slow to recover despiteclinically well controlled inflammatory joint symptomswith first line non-biologic DMARD therapies, with orFeehan et al. BMC Musculoskeletal Disorders  (2017) 18:521 Page 11 of 13without additional glucocorticoid medications. Althoughpreliminary, findings suggest that further conservative orpharmacological treatments that address underlying bonehealth in early RA may serve to address the higher risk forfracture for those with RA compared with peers. Furtherresearch is also warranted to better understand ‘how early’changes in bone microstructure may be associated withbiomarkers of bone turnover in early RA and the naturalprogression of RA disease [51]. Research that evaluatesfactors associated with longer term loss in bone micro-structure and fracture incidence in RA are also needed.Clinically, our findings support the importance of earlyand aggressive treatment and proactive monitoring andtargeted management of bone health and fracture risk inindividuals living with RA [52].Additional fileAdditional file 1: Table S4. HR-pQCT Time (Baseline vs 12-months)Main Effects Summary. Summary of data and statistical results for theTime main (Baseline vs 12-months) effect analyses. Table S5. HR-pQCTInteraction [Disease (RA vs NRA) x Time (Baseline vs 12-months)] MainEffects Summary. Summary of data and statistical results for theInteraction (Disease x Time) main effect analyses. (XLSX 22 kb)AbbreviationsACPA: Anti-Citrullinated Peptide Autoantibodies; ACR/EULAR: AmericanCollege of Rheumatology / European League Against Rheumatism; Anti-TNF: Anti-Tumor Necrosis Factor; BMI: Body Mass Index; DMARD: DiseaseModifying Antirheumatic Drug; FRAX®: Fracture Risk Assessment Tool(Registered); HR-pQCT: High Resolution – peripheral Quantitative ComputedTomography; MH: Metacarpal Head; mHAQ: Stanford Health AssessmentQuestionnaire - Modified; NRA: Non-Rheumatoid Arthritis; RA: RheumatoidArthritis; RF: Rheumatoid Factor; SMI: Structural Model Index; UUD: Ultra-Ultra-DistalAcknowledgementsThe authors would like to thank the following people for their support withrecruitment for, and evaluation of participants in this study. Rheumatologists:Drs Aviva, Chan, Collins, Jamal, Kelsall, Kerhani, Koehler, Ramsden, Shojania.Patient Collaborator: G Whitehead (Arthritis Patient Advisor Board -ArthritisResearch Canada). Research Assistants: C MacDonald, E Carruthers.FundingThe work was supported in part by a Michael Smith Foundation for HealthResearch (British Columbia, Canada) Post-Doctoral Fellowship Award for thefirst author (LF) [ST-PDF-02860(09–1)].Availability of data and materialsThe aggregate data and statistical analyses are included in this publishedarticle [and its supplementary information files]. Raw data are available fromthe corresponding author on reasonable request.Authors’ contributionsLF was primarily responsible for the conception and design, acquisition ofdata, data analyses and interpretation of data results; LL and HM supportedthe planning and interpretation of the data, drafting of the manuscript andhave given final approval for this manuscript to be submitted for publication.Ethics approval and consent to participateThis study received ethics approval from the Clinical Ethics Review Board[H10–01170] at the University of British Columbia, Vancouver, Canada and allparticipants provided written consent.Consent for publicationN/ACompeting interestsThe authors declare that they have no competing interests.Publisher’s NoteSpringer Nature remains neutral with regard to jurisdictional claims inpublished maps and institutional affiliations.Author details1Department of Physical Therapy, University of British Columbia, Vancouver,BC, Canada. 2Arthritis Research Canada, 5591 No. 3 Road, Richmond, BC V6X2C7, Canada. 3Department of Orthopedics and Family Practice, Centre forHip Health and Mobility, University of British Columbia, Vancouver, BC,Canada.Received: 29 June 2017 Accepted: 1 December 2017References1. Bombardier C, Hawker G, Mosher D. In: the impact of arthritis in Canada:today and over the next 30 years. Arthritis Alliance of Canada. 2011:1–52.http://www.arthritisalliance.ca/images/PDF/eng/Initiatives/20111022_2200_impact_of_arthritis.pdf. Accessed 29 Sept 20172. Innala L, Sjöberg C, Möller B, Ljung L, Smedby T. Södergren et al. co-morbidity in patients with early rheumatoid arthritis - inflammation matters.Arthritis Res Ther. 2016;18:33.3. Kim D, et al. Incidence and risk factors of fractures in patients withrheumatoid arthritis: an Asian prospective cohort study. Rheumatol Int.2016;36(9):1205–14.4. Yamamoto Y, Turkiewicz A, Wingstrand H, Englund M. Fragility fractures inpatients with rheumatoid arthritis and osteoarthritis compared with thegeneral population. J Rheumatol. 2015;42(11):2055–8.5. Brennan SL, Toomey L, Kotowicz MA, Henry MJ, Griffiths H, Pasco JA.Rheumatoid arthritis and incident fracture in women: a case-control study.BMC Musculoskelet Disord. 2014;15:13.6. Amin S, Gabriel SE, Achenbach SJ, Atkinson EJ, Melton LJ 3rd. Are youngwomen and men with rheumatoid arthritis at risk for fragility fractures?A population-based study. J Rheumatol. 2013;40(10):1669–76.7. Nevius E, Gomes AC, Pereira JP. Inflammatory cell migration in rheumatoidarthritis: a comprehensive review. Clin Rev Allergy Immunol. 2016;51(1):59–78.8. Goldring SR. Inflammatory signaling induced bone loss. Bone. 2015;80:143–9.9. Rosa N, Simoes R, Magalhães FD, Marques AT. From mechanical stimulus tobone formation: a review. Med Eng Phys. 2015;37(8):719–28.10. Kazakia GJ, Tjong W, Nirody JA, Burghardt AJ, Carballido-Gamio J, Patsch JM,et al. The influence of disuse on bone microstructure and mechanicsassessed by HR-pQCT. Bone. 2014;63:132–40.11. Balasubramanian A, Wade SW, Adler RA, Lin CJ, Maricic M, O’Malley CD,et al. Glucocorticoid exposure and fracture risk in patients with new-onsetrheumatoid arthritis. Osteoporos Int. 2016;27(11):3239–49.12. Roussy JP, Bessette L, Bernatsky S, Rahme E, Lachaine J. Biologic disease-modifying anti-rheumatic drugs and the risk of non-vertebral osteoporoticfractures in patients with rheumatoid arthritis aged 50 years and over.Osteoporos Int. 2013;24(9):2483–92.13. Zerbini CA, Clark P, Mendez-Sanchez L, Pereira RM, Messina OD, Uña CR,et al. Biologic therapies and bone loss in rheumatoid arthritis. OsteoporosInt. 2017;28(2):429–46.14. Carpenter L, Nikiphorou E, Sharpe R, Norton S, Rennie K, Bunn F, et al. Haveradiographic progression rates in early rheumatoid arthritis changed? Asystematic review and meta-analysis of long-term cohorts. Rheumatology.2016;55(6):1053–65.15. Burge AJ, Nwawka OK, Berkowitz JL, Potter HG. Imaging of inflammatoryarthritis in adults: status and perspectives on the use of radiographs,ultrasound, and MRI. Rheum Dis Clin N Am. 2016;42(4):561–85.16. Alves C, Colin EM, Oort WJ, Van SJP, JMW H, Luime JJ. Periarticularosteoporosis: a useful feature in the diagnosis of early rheumatoid arthritis?Reliability and validity in a cross-sectional diagnostic study using dual-energy X-ray absorptiometry. Rheumatology. 2011;50(12):2257–63.17. Pfeil A, Haugeberg G, Renz DM, Reinhardt L, Jung C, Franz M, et al. DigitalX-ray radiogrammetry and its sensitivity and specificity for the identificationFeehan et al. BMC Musculoskeletal Disorders  (2017) 18:521 Page 12 of 13of rheumatoid arthritis-related cortical hand bone loss. J Bone Miner Metab.2017;35(2):192–8.18. Nagaraj S, Finzel S, Stok KS, Barnabe C. SPECTRA collaboration. High-resolution peripheral quantitative computed tomography imaging in theassessment of periarticular bone of metacarpophalangeal and wrist joints.J Rheumatol. 2016;43(10):1921–34.19. Feehan L, Buie H, Li L, McKay H. A customized protocol to assess bonequality in the metacarpal head, metacarpal shaft and distal radius: a highresolution peripheral quantitative computed tomography precision study.BMC-Musculoskeletal Disorders. 2013;14(1):367.20. Barnabe C, Feehan L. SPECTRA (study GrouP for XTrEme-CT in RA). High-resolution peripheral quantitative computed tomography imaging protocolfor metacarpophalangeal joints in inflammatory arthritis: the SPECTRAcollaboration. J Rheumatol. 2012;39(7):1494–5.21. Fouque-Aubert A, Boutroy S, Marotte H, Vilayphiou N, Bacchetta J, MiossecP, et al. Assessment of hand bone loss in rheumatoid arthritis by high-resolution peripheral quantitative CT. Ann Rheum Dis. 2010;69:1671–6.22. Barnabe C, Szabo E, Martin L, Boyd SK, Barr SG. Quantification of small jointspace width, periarticular bone microstructure and erosions using high-resolution peripheral quantitative computed tomography in rheumatoidarthritis. Clin Exp Rheumatol. 2013;31:243–50.23. Zhu TY, Griffith JF, Qin L, Hung VW, Fong TN, SK A, et al. Structure andstrength of the distal radius in female patients with rheumatoid arthritis: acase-control study. J Bone Miner Res. 2013;28(4):794–806.24. Zhu TY, Griffith JF, Qin L, Hung VW, Fong TN, SK A, et al. Alterations of bonedensity, microstructure, and strength of the distal radius in male patientswith rheumatoid arthritis: a case-control study with HR-pQCT. J Bone MinerRes. 2014;29(9):2118–29.25. Kocijan R, Finzel S, Englbrecht M, Engelke K, Rech J, Schett G. Decreasedquantity and quality of the periarticular and nonperiarticular bone inpatients with rheumatoid arthritis: a cross-sectional HR-pQCT study.J Bone Miner Res. 2014;29(4):1005–14.26. Yang H, Yu A, Burghardt AJ, Virayavanich W, Link TM, Imboden JB, et al.Quantitative characterization of metacarpal and radial bone in rheumatoidarthritis using high resolution - peripheral quantitative computedtomography. Int J Rheum Dis. 2017;20(3):353–62.27. Kleyer A, Finzel S, Rech J, Manger B, Krieter M, Faustini F, et al. Bone lossbefore the clinical onset of rheumatoid arthritis in subjects withanticitrullinated protein antibodies. Ann Rheum Dis. 2014;73(5):854–60.28. Bykerk VP, Akhavan P, Hazlewood GS, Schieir O, Dooley A, Haraoui B, et al.Canadian rheumatology association. Canadian rheumatology associationrecommendations for pharmacological management of rheumatoid arthritiswith traditional and biologic disease-modifying antirheumatic drugs.J Rheumatol. 2012;39(8):1559–82.29. Singh JA, Saag KG, Bridges SL Jr, Akl EA, Bannuru RR, Sullivan MC, et al. 2015American College of Rheumatology Guideline for the treatment ofrheumatoid arthritis. Arthritis Rheumatol. 2016;68(1):1–26.30. Smolen JS, Breedveld FC, Burmester GR, Bykerk V, Dougados M, Emery P,et al. Treating rheumatoid arthritis to target: 2014 update of therecommendations of an international task force. Ann Rheum Dis.2016;75(1):3–15.31. Aletaha D, Neogi T, Silman AJ, Funovits J, Felson DT, Bingham CO 3rd, et al.2010 rheumatoid arthritis classification criteria: an American College ofRheumatology/European league against rheumatism collaborative initiative.Ann Rheum Dis. 2010;69(9):1580–8.32. Scott IC, Scott DL. Joint counts in inflammatory arthritis. Clin ExpRheumatol. 2014;32(5 Suppl 85):S-7–12.33. Maska L, Anderson J, Michaud K. Measures of functional status and qualityof life in rheumatoid arthritis: health assessment questionnaire disabilityindex (HAQ), modified health assessment questionnaire (MHAQ),multidimensional health assessment questionnaire (MDHAQ), healthassessment questionnaire II (HAQ-II), improved health assessmentquestionnaire (improved HAQ), and rheumatoid arthritis quality of life(RAQoL). Arthritis Care Res (Hoboken). 2011;63(Suppl. 11):S4–13.34. JD Douketis G, Paradis H, Keller C, Martineau NCD. Risk factor collaboration.“Trends in adult body-mass index in 200 countries from 1975 to 2014: apooled analysis of 1698 population-based measurement studies with 19· 2million participants”. Lancet. 2016;387:1377–96.35. Kanis JA, McCloskey E, Johansson H, Oden A, Leslie WDFRAX. ® with andwithout bone mineral density. Calcif Tissue Int. 2012;90(1):1–3.36. Cosman F. Anabolic and antiresorptive therapy for osteoporosis:combination and sequential approaches. Curr Osteoporos Rep.2014;12(4):385–95.37. Pope JE, Khanna D, Norrie D, Ouimet JM. The minimally importantdifference for the health assessment questionnaire in rheumatoid arthritisclinical practice is smaller than in randomized controlled trials. J Rheumatol.2009;36(2):254–9.38. Jilka RL, O’Brien CA. The role of osteocytes in age-related bone loss. Currentosteoporosis reports. 2016;14(1):16–25.39. Alvarenga JC, Fuller H, Pasoto SG, Pereira RM. Age-related reference curvesof volumetric bone density, structure, and biomechanical parametersadjusted for weight and height in a population of healthy women: an HR-pQCT study. Osteoporos Int. 2017;28(4):1335–46.40. Kawalilak CE, Johnston JD, Cooper DM, Olszynski WP, Kontulainen SA. Roleof endocortical contouring methods on precision of HR-pQCT-derivedcortical micro-architecture in postmenopausal women and young adults.Osteoporos Int. 2016;27(2):789–96.41. Thomsen JS, Jensen MV, Niklassen AS, Ebbesen EN, Brüel A. Age-relatedchanges in vertebral and iliac crest 3D bone microstructure—differencesand similarities. Osteoporos Int. 2015;26(1):219–28.42. Burt LA, Liang Z, Sajobi TT, Hanley DA, Boyd SK. Sex-and site-specificnormative data curves for HR-pQCT. J Bone Miner Res. 2016;31(11):2041–7.43. Bala Y, Bui QM, Wang XF, Iuliano S, Wang Q, Ghasem-Zadeh A, et al.Trabecular and cortical microstructure and fragility of the distal radius inwomen. J Bone Miner Res. 2015;30(4):621–9.44. Takayanagi H. Osteoimmunology in 2014: two-faced immunology - fromosteogenesis to bone resorption. Nat Rev Rheumatol. 2011;11(2):74–6.45. Pietschmann P, Mechtcheriakova D, Meshcheryakova A, Föger-Samwald U,Ellinger I. Immunology of osteoporosis: a mini-review. Gerontology.2015;62(2):128–37.46. Lacaille D, Anis AH, Guh DP, Esdaile JM. Gaps in care for rheumatoidarthritis: a population study. Arthritis Care Res (Hoboken). 2005;53(2):241–8.47. Jamal S, Alibhai SM, Badley EM, Bombardier C. Time to treatment for newpatients with rheumatoid arthritis in a major metropolitan city. J Rheumatol.2011;38(7):1282–8.48. Schmajuk G, Trivedi AN, Solomon DH, Yelin E, Trupin L, Chakravarty EF, et al.Receipt of disease-modifying antirheumatic drugs among patients withrheumatoid arthritis in Medicare managed care plans. JAMA.2011;305(5):480–6.49. Kawalilak CE, Johnston JD, Olszynski WP, Kontulainen SA. Least significantchanges and monitoring time intervals for high-resolution pQCT-derivedbone outcomes in postmenopausal women. J Musculoskelet NeuronalInteract. 2015;15(2):190–6.50. Jorgenson BL, Buie HR, McErlain DD, Sandino C, Boyd SKA. Comparison ofmethods for in vivo assessment of cortical porosity in the humanappendicular skeleton. Bone. 2015;73:167–75.51. Zerbini CAF, Clark P, Mendez-Sanchez L, et al. Biologic therapies and boneloss in rheumatoid arthritis. Osteoporos Int. 2017;28(2):429–46.52. Mullen MB, Saag KG. Evaluating and mitigating fracture risk in establishedrheumatoid arthritis. Best Pract Res Clin Rheumatol. 2015;29(4):614–27.•  We accept pre-submission inquiries •  Our selector tool helps you to find the most relevant journal•  We provide round the clock customer support •  Convenient online submission•  Thorough peer review•  Inclusion in PubMed and all major indexing services •  Maximum visibility for your researchSubmit your manuscript atwww.biomedcentral.com/submitSubmit your next manuscript to BioMed Central and we will help you at every step:Feehan et al. BMC Musculoskeletal Disorders  (2017) 18:521 Page 13 of 13

Cite

Citation Scheme:

        

Citations by CSL (citeproc-js)

Usage Statistics

Share

Embed

Customize your widget with the following options, then copy and paste the code below into the HTML of your page to embed this item in your website.
                        
                            <div id="ubcOpenCollectionsWidgetDisplay">
                            <script id="ubcOpenCollectionsWidget"
                            src="{[{embed.src}]}"
                            data-item="{[{embed.item}]}"
                            data-collection="{[{embed.collection}]}"
                            data-metadata="{[{embed.showMetadata}]}"
                            data-width="{[{embed.width}]}"
                            async >
                            </script>
                            </div>
                        
                    
IIIF logo Our image viewer uses the IIIF 2.0 standard. To load this item in other compatible viewers, use this url:
http://iiif.library.ubc.ca/presentation/dsp.52383.1-0361790/manifest

Comment

Related Items