Essay Writing Service

A Clinical Research Study on Trapeziometacarpal Osteoarthritis

A CLINICAL RESEARCH STUDY ON TRAPEZIOMETACARPAL OSTEOARTHRITIS

Table of Contents

List of Table and Figures

Summary

1.0 Introduction

2.0 Rationale behind the Study

3.0 Study Design

3.1 Study Type

3.1.1 Sample Size

3.1.2 Study Stages

3.2 Patient-reported Outcome Measures

3.2.1 McGill Pain Questionnaire Short Form (MPQ-SF)

3.2.2 Quick DASH (Disability of the Arm, Shoulder and Hand)

3.2.3 Pain Catastrophizing Scale (PCS)

3.2.4 Homunculus

3.2.5 12-Item Short Form Questionnaire (SF-12)

3.2.6 EuroQol-5D (EQ-5D)

3.2.7 Hospital Anxiety and Depression Scale (HADS)

3.2.8 Trapeziometacarpal Arthrosis Symptom and Disability Questionnaire (TASD)

4.0 Measurement of Molecular and Cellular Biomarkers

4.1 Procedure and Technique for Harvesting Synovial Fluid and Synovium

4.2 Cellular Biomarkers

4.3 Biochemical Markers

5.0 Conclusions

6.0 Recommendations

References

 

 

 

List of Table and Figures

Figure 1: Schematic of Study Stage   …………………………………………………………..   6

Table 1:  A list of biomarkers of interest ……………………………………………………… 11

Summary

This report entitled “A Clinical Research Study on Trapeziometacarpal Osteoarthritis” and the report performs an overview  of the recruitment steps analysis in a clinical trial and the benefit of doing a biomarkers study on trapeziometacarpal osteoarthritis(TM-OA). The purpose of this report is to show that biochemical and cellular biomarkers express in joint and systemically in patients whether they are conservative or surgical patients. This report includes some insights I have gathered as clinical researcher at University Health Network.

The main focus of the report is to analyze and showcase the procedures required to evaluate patients that are enrolled in a surgical clinical study. The study includes a rationale behind the study, patients outcome measurements to evaluate pain levels and molecular and cellular biomarkers to better understand TM-OA.

Highlights of conclusions includes

  •                  TM-OA is a very painful disease and reduces hand mobility
  •                  Understanding of cellular and biochemical make-up may lead to delaying hand OA
  •                  A lengthy study allows to improve overall proof of concept and improve.
  •                  Large pool of participants is necessary for the success of a clinical study

Highlights of recommendation:

  •                  Patients will appreciate alternative treatments to surgery that enhance  hand mobility in the long term
  •                  Genetics testing should also be conducted to increase further findings
  •                  As population ages, arthritis research will be more lucrative for private firms .
  •                  Have one clinician work on the project will reduce the amount of  bias drastically

1.0 Introduction

OA of the TM joint is a debilitating condition imposing significant functional limitations for vocational and avocational activities.  Population studies have identified that radiographic OA is present in 4-33% of patients (Dahaghin et al., 2005), demonstrating a disconnect from symptomatic TM OA which arises in about 1 in 30 individuals with women being more commonly afflicted  (Moriatis et al. 2014).  This basis for this disconnect between radiographic and symptomatic OA is not clear. Due to the aging population, the prevalence of symptomatic hand OA is projected to increase over the next two decades creating an additional burden on the healthcare system and creating functional deficit for a larger cohort of the population (Cho et al, 2015).

A tremendous interest exists within the arthritis research community to establish a better understanding of the role of systemic and joint-specific biomarkers in patients with symptomatic OA for prognostic and personalized therapeutic and regenerative purposes. A biomarker is a measurable molecular or cellular marker of a normal biologic pathway, a pathogenic processes, or a demonstration of a response to therapeutic intervention (Biomarkers Definitions Working, 2001). Characterization of OA-related biomarkers has the potential to describe early disease mechanisms and OA phenotypes that could be targeted for prevention of joint degeneration, improve clinical trial designs, and provide novel means to monitor patient response to treatments (Cooper et al., 2013; Lane et al., 2015). Standard reference intervals for soluble OA-related biomarkers have been recently published to act as control values for future serum biomarker studies (Kraus et al. 2017) ; meanwhile, novel biomarkers are continuously being identified and linked to OA along with developments of new technologies for their detection and quantification (Mobasheri et al., 2017) These developments are exciting in the face of an increasing prevalence of symptomatic OA.

Many OA-related serum biomarker studies have focused on weight bearing joints in the lower extremity and the role of obesity and indirectly the changes in metabolic and inflammatory states that result in cartilage degeneration (Henrotin, Sanchez, Bay-Jensen, & Mobasheri, 2016; Yusuf, 2012). To better examine metabolic changes in isolation from the biomechanical effect of weight bearing and obesity, there has been some research examining systemic factors, specifically adipocytokines, in hand OA (Choe et al., 2012) .

Inflammatory cells, particularly monocytes/macrophages (Ms) are abundantly present in OA synovium (de Lange-Brokaar et al., 2012) and involved in its progression (Blom et al., 2007). Although there is limited research on Ms in OA, it has been shown that depleting synovial macrophages modulates OA progression in a murine OA model (Blom et al., 2004) suggesting that Ms are involved in OA development and therapeutic approaches to decrease pro-inflammatory Ms are worth pursuing.

This report focus on the rationale behind conducting a clinical biomarker analysis in thumb trapeziometacarpal OA to better understand the role of inflammatory cells in this OA phenotype. The study includes the study design, cellular biomarkers interests and statistical and data component of the project.

2.0 Rationale behind the Study

The rationale behind this study is that to date, biomarker studies for hand OA have been limited and measured only in the serum, rather than correlating joint-specific molecular or cellular biomarker changes to patient-reported pain or radiographs. (Choe et al., 2012) . There is no published research examining biomarkers both at the level of the affected TM joint (e.g. synovial fluid and resident synovial cells) and little relating TM joint pain to systemic biomarkers. In larger weight bearing joints, synovial fluid studies have demonstrated changes in pro-inflammatory biomarkers related to worsening symptoms and radiographic progression in addition to increased macrophage activation (Daghestani et al. 2015). By understanding the joint-specific changes that occur at both molecular and cellular biomarkers we can get a better understanding of the mechanism of disease at the joint level, potential local disease modifying agents and how these changes relate to those demonstrated on a systemic level; yet, substantial knowledge gaps exist regarding differential molecular and cellular biomarker these patients that could provide a personalized therapeutic or regenerative approach for treatment of symptomatic OA of the hand. (Blom et al., 2007)

3.0 Study Design

The Arthritis program at UHN understand the impact that hand OA has in improving quality of life for all Canadians. This study allows to investigate this issue in detail.

3.1 Study Type

This research is a pilot longitudinal study of TM OA patients undergoing standard conservative treatment options (e.g. splinting, cortisone injections, physiotherapy) and surgical  intervention such as trapeziectomy (removal of the trapezium bone) . (Hudak et al, 1996). Indications for TM joint trapeziectomy include: persistent pain that limits normal hand function as assessed by patient report and clinical parameters including limited range of motion, deformity, grip and pinch strengths; failure of conservative measures; and capacity to give informed consent for operative intervention. (Hudak et al, 1996).

Subjects for this study were also recruited from a subset of participants already recruited from a data and tissue banking project with similar data collection structure and patient population. Additionally, equivalent data from existing subjects from the Arthritis programs other project were used to supplement the cohort recruited for this study pending their eligibility after review.

3.1.1 Sample Size

Approximately 60 TM trapeziectomy procedures are performed at Toronto Westernt each year (dados, 2017). Assuming a recruitment rate of 75% and accounting for incomplete data collection (e.g. incomplete synovial fluid samples) we estimate to recruit 110 patients to reach our expected 80 participants for our analysis over a 30 month recruitment period. Banked data and tissues from existing subject profiles stored in the Arthritis Program Project may be used to supplement this cohort.

3.1.2 Study Stages

Study procedures and data collection commence at any pre-operative point a prospective participant is determined to meet eligibility criteria for participation. Subjects who are directed towards conservative treatments will immediately fill out a baseline questionnaire, undergo the clinical tests and provide baseline specimens. At every subsequent routine follow-up visit, to a maximum of 6 per year, subjects will continue to complete identical follow-up procedures. (Melzack, 1987)

Figure 1. Schematic of Study Stages

Screening & Recruitment

  • Eligibility criteria met
  • Informed consent given

Conservative Treatment

  • Questionnaire
  • Blood & Urine
  • Clinical Tests

Surgical Intervention (Trapeziectomy)

  • Questionnaire
  • Blood & Urine
  • Clinical Tests
  • Surgical Tissue

Follow-Up Visits

(Up to 6x per Year)

  • Questionnaire
  • Blood & Urine
  • Clinical Tests

Follow-Up Visits

6, 12, 26, 52 Weeks

  • Questionnaire
  • Blood & Urine
  • Clinical Tests

Follow-up

Follow-up

Opts for surgery

52 Weeks Post-Op

Study Endpoint

Subjects who fail to respond to conservative treatment methods and/or opt to receive surgical intervention will be transferred to the surgical arm of the study. ( Osman et al., 2000) A set of procedures identical to the conservative treatment arm of the study will be completed within 12 weeks of the scheduled operative date. Intra-operative bio-specimen retrieval will occur at surgical intervention.  A set of questionnaires and similar procedures will be conducted at post-operative standard of care follow-up visits, namely at 6, 12, 26 and 52 weeks after the surgery. (check figure 1)

3.2 Patient-reported Outcome Measures

The outcome measures were completed by subjects via electronic methods of there choice (i.e. tablet, smart phone, computer etc.) using the DADOS platform. Additionally, data outcome measures obtained from subjects who also participate in the Arthritis Program project may have that data collected and used for this study. ( Gracely et al., 2004)

3.2.1 McGill Pain Questionnaire Short Form (MPQ-SF)

The MPQ-SF is comprised of pain descriptors, pain intensity visual analog scale (VAS) and present pain intensity (Melzack, 1975). Each pain descriptor is ranked on a scale from 0 (none) to 10 (severe). The values are summated to calculate a pain rating index and a higher index reflects more pain. Subjects are also asked to rank their pain intensity on a 10 cm VAS. The subject’s present pain level is assessed on a scale of 0 (no pain) to 5 (excruciating) with a higher number indicating more pain. Good validity and reliability have been shown with the MPQ-SF (Melzack, 1987).

3.2.2 Quick DASH (Disability of the Arm, Shoulder and Hand)

The DASH was developed to assess disability by self-report of physical function and symptoms in patients with upper limb musculoskeletal disorders (Beaton et al., 2001)The Quick DASH is a truncated version with 11 items, and each item is ranked on a 5-point scale ranging from “no difficulty” to “unable”(Beaton, Wright, Katz, & Upper Extremity Collaborative, 2005). A higher Quick DASH score reflects a greater degree of disability. This questionnaire has been shown to have good validity in rheumatoid arthritis patients (Ochi et al., 2015).

3.2.3 Pain Catastrophizing Scale (PCS)

The PCS is designed to measure the degree of exaggerated negative thinking relative to pain (Sullivan, Lynch, & Clark, 2005). It is a 13 item questionnaire and subjects are asked to indicate the degree, on a scale from 0 (not at all) to 4 (all the time), that they experience the 13 thoughts/feelings when they experience pain (Cano, Leonard, & Franz, 2005). Three subscales (rumination, magnification, helplessness) and a total score can be calculated. A higher score indicates a higher degree of catastrophizing. This questionnaire has been shown to have good validity and reliability (Chibnall & Tait, 2005)

3.2.4 Homunculus

The homunculus form is a tool designed to document chronic joint symptoms. It is a self-reported form asking, “Thinking about the past 12 months, please indicate below in which joints you have experienced pain, swelling, and/or stiffness on most days for at least a month”.  A standard homunculus diagram is presented to the subject with joints depicted as bubbles, which the patient marks if the corresponding joint fits the above description. It has been previously used in osteoarthritis-focused studies (Bellamy et al., 1999).

3.2.5 12-Item Short Form Questionnaire (SF-12)

The SF-12 is a self-reported questionnaire constructed from the 36-item equivalent in order to reduce completion times and thus patient burden (Ware, Kosinski, & Keller, 1996). It includes a subset of questions from the physical health component and mental health components of the original SF-36 questionnaire and retains similar scoring outcomes (Jenkinson et al., 1997). Each question is weighted equally with lower scores indicating worse health.

3.2.6 EuroQol-5D (EQ-5D)

The EQ-5D is a descriptive system used to measure overall health in 5 dimensions:  mobility, self-care, usual activities, pain/discomfort and anxiety/depression (EuroQol, 1990). Included is the Visual Analog Scale, which gives a quantitative value to the individual’s overall health state. There is evidence to suggest the EQ-5D is suitable as a measure of health for individuals with rheumatoid arthritis of the hand (Dritsaki et al., 2017).

3.2.7 Hospital Anxiety and Depression Scale (HADS)

HADS is a 14 question survey constructed for the purposes of assessing for anxiety disorders and depression (Zigmond & Snaith, 1983). It is divided into a depression subscale and anxiety subscale, each composed of 7 questions. Previous work has demonstrated the HADS to have strong validity in a broad spectrum of populations including arthritic patients (Axford et al., 2010)

3.2.8 Trapeziometacarpal Arthrosis Symptom and Disability Questionnaire (TASD)

TASD is a questionnaire for specific assessment of symptoms and disability at the TMC joint (Becker, Teunis and Ring, 2016). The TASD has 12 items to assess symptoms and disability demonstrating good internal consistency and convergent validity.

4.0 Measurement of Molecular and Cellular Biomarkers

Study participants provide 6 ml whole blood specimens (anti-coagulated) and up to 100 ml urine samples upon enrolling into the study and at all future follow-up visits to the clinic (to a maximum of 6 collections per year). Subjects that consent to undergo TM arthroplasty surgery will provide an identical sample set within 12 weeks prior to their operation. Venous specimens will be obtained from the antecubital fossa into K2 EDTA vacutainer tubes prior to any intervention. Vacutainer specimens will be handled according to manufacturer’s protocol prior to lab processing. Urine specimens will be produced into sterile containers and stored on ice or at 4 degrees Celsius until processing.

Biomarkers were measured in blood and synovial fluid (SF) collected on the day of surgery and will be stored in the UHN Arthritis Program Tissue Bank, although cellular analyses will be performed on fresh samples. All biomarkers to be measured are listed in Table 1.

Pro-/anti-Inflammatory Cytokines Metabolic Pain Inflammation- Mediating Cells
IFN-ϒ Adiponectin PGE2 Monocytes
IL-1β Leptin Substance P T-cells
IL-1RA Norepinephrine NK cells
IL-6 Neutrophils
IL-8
IL-10 

IL-12

TNF- α
MCP-1
MIP-1β
Table 1. A list of biomarkers of interest.

4.1 Procedure and Technique for Harvesting Synovial Fluid and Synovium

A subset of patients enrolled in this study will likely undergo a trapeziectomy procedure, which is standard at our institution for end-stage TM OA.  In brief, a dorso-radial incision is made over the TM joint.  (Li et al., 2016) Upon exposure of the capsule, a 25-gauge needle is placed within the joint and an aspirate of the joint is attempted.  If there is an insufficient synovial fluid (100ul required for analysis), 200ul of normal saline is flushed in the joint and then re-aspirated.  After opening the capsule, synovium and capsule are harvested requiring a 5mmx5mm specimen.

Once the specimens are harvested, a standard metacarpal resuspension and interpositional arthroplasty are performed using half of the flexor carpi radialis or a slip of abductor pollicis longus. (Li et al., 2016)

Soft tissues collected from surgery to be used for immediate cellular analysis will be transported to the lab at 4 degrees Celsius. The remaining tissues will be placed in cryovials, flash frozen immediately in a liquid nitrogen dewer and later stored in liquid nitrogen tanks. (Nakamura et al., 2016)

4.2 Cellular Biomarkers

SF cells are isolated by centrifugation, and the SF supernatant is stored for analyses of cytokines. Control peripheral blood mononuclear cells (PBMCs) are isolated by density gradient centrifugation as described (Abeles et al., 2012). SFCs and PBMCs are characterized using flow cytometry for total T cell, monocyte, neutrophil and NK cell frequency; monocyte subtypes (CD14+CD16+, CD14+CD16neg, CD14lowCD16+), as described (Abeles et al., 2012); T helper cells frequency and stage of activation using CD69, CD25 and HLADR (Afeltra et al., 1997). The synovial capsules will be digested using hyaluronidase/collagenase for 2 hours at 37°C. Cell resulting from the digestion will then be characterized for macrophages and T cells. Macrophages will be characterized using CD163, CD206, CD14, CD16, HLADR, CD86 and CCR2. T cells will be characterized as described above. (Abeles et al., 2012)

4.3 Biochemical Markers

Three categories of biomarkers are analyzed: metabolic, inflammatory, and pain.  Biomarkers to be tested are outlined in Table 1. The pro-/anti-inflammatory cytokines and metabolic markers are analyzed using a clinically validated MAGPIX multiplexing instrument from Luminex.  (Lao et al, 2007) The pain markers are quantified separately using single-plex ELISA assays.  If none of these biomarkers show any significant correlation in this study, the samples will be subjected  to other potential biomarker candidates including circulating microRNAs and metabolomics as identified by Kapoor’s recent findings (Gandhi et al, 2016).

To summarize, as in any good scientific protocol, results of testing has to be accessible. For anyone to see in the future.

 

5.0 Conclusions

TM-OA is a very painful degenerative disease and hinders the amount of activity someone can appreciate even post-surgery finding alternatives are crucial. Research has been very promising in the field of cellular biomarker analysis and biochemical marker analysis.

Understanding the cellular and biochemical make up will allow to delay the symptoms in a more localized manner, hence increasing patient’s ability to continue working without going through surgery.

A very rigorous study design with a large pool of participants some with early onset OA allows researcher to determine the disease progression using functional strength measurements, outcome measures and basic science experiments.

Follow-ups with patients over long period of times allows clinicians to understand and tweak any bias that the project may have in order to improve and simplify. Patients outcome measures is a very important tool for clinicians as it gives a better understand of patients pain levels which may differ from radiographic imaging and cellular analysis.

From a scientific perspective running a cellular biomarker and biochemical marker allows clinicians to better understand the role of various cytokines resulting osteoarthritis and gives a clearer indication on what drugs may be used to reduce it.

6.0 Recommendations

Finding alternatives to surgeries will allow more freedom to patients to continue having a normal life without the encumbrance of having a loss of joint function and increasing time from conservative techniques to surgery will allow clinicians to look at other alternatives.

Cellular and biochemical makeup of hand OA should not be the only focus of the study but also other joints from the same patient to compare and contrast the underlying causes of the disease.

Follow-ups may vary but  having various clinician  working on the same project will hinder it is effectiveness and hence having one person dedicated to the study will improve patient recruitment as well as have an in-depth understanding of the patient outcome measurements.

Clinicians running cellular and biochemical markers should not limit themselves on those two type of experiments but also may be run genetics tests to understand if this debilitating disease may be as a results of some genetic defects.

As the population is aging, arthritis will become more economical viable for private firms to endeavour and further its research and will allow a better in-depth understanding of this condition

References

Abeles, R. D., McPhail, M. J., Sowter, D., Antoniades, C. G., Vergis, N., Vijay, G. K., . . . Vergani, D. (2012). CD14, CD16 and HLA-DR reliably identifies human monocytes and their subsets in the context of pathologically reduced HLA-DR expression by CD14(hi) /CD16(neg) monocytes: Expansion of CD14(hi) /CD16(pos) and contraction of CD14(lo) /CD16(pos) monocytes in acute liver failure. Cytometry A, 81(10), 823-834. doi:10.1002/cyto.a.22104

Afeltra, A., Galeazzi, M., Sebastiani, G. D., Ferri, G. M., Caccavo, D., Addessi, M. A., . . . Bonomo, L. (1997). Coexpression of CD69 and HLADR activation markers on synovial fluid T lymphocytes of patients affected by rheumatoid arthritis: a three-colour cytometric analysis. Int J Exp Pathol, 78(5), 331-336.

Axford, J., Butt, A., Heron, C., Hammond, J., Morgan, J., Alavi, A., . . . Bland, M. (2010). Prevalence of anxiety and depression in osteoarthritis: use of the Hospital Anxiety and Depression Scale as a screening tool. Clin Rheumatol, 29(11), 1277-1283. doi:10.1007/s10067-010-1547-7

Beaton, D. E., Katz, J. N., Fossel, A. H., Wright, J. G., Tarasuk, V., & Bombardier, C. (2001). Measuring the whole or the parts? Validity, reliability, and responsiveness of the Disabilities of the Arm, Shoulder and Hand outcome measure in different regions of the upper extremity. J Hand Ther, 14(2), 128-146.

Beaton, D. E., Wright, J. G., Katz, J. N., & Upper Extremity Collaborative, G. (2005). Development of the QuickDASH: comparison of three item-reduction approaches. J Bone Joint Surg Am, 87(5), 1038-1046. doi:10.2106/JBJS.D.02060

Becker, S. J., Teunis, T., Ring, D., & Vranceanu, A. M. (2016). The Trapeziometacarpal Arthrosis Symptoms and Disability Questionnaire: Development and Preliminary Validation. Hand (N Y), 11(2), 197-205. doi:10.1177/1558944715627239

Bellamy, N., Klestov, A., Muirden, K., Kuhnert, P., Do, K. A., O’Gorman, L., & Martin, N. (1999). Perceptual variation in categorizing individual peripheral joints for the presence or absence of osteoarthritis using a standard homunculus: observations based on an australian twin registry study of osteoarthritis. Inflammopharmacology, 7(1), 37-46. doi:10.1007/s10787-999-0024-x

Biomarkers Definitions Working, G. (2001). Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther, 69(3), 89-95. doi:10.1067/mcp.2001.113989

Bjelland, I., Dahl, A. A., Haug, T. T., & Neckelmann, D. (2002). The validity of the Hospital Anxiety and Depression Scale. An updated literature review. J Psychosom Res, 52(2), 69-77.

Blom, A. B., van Lent, P. L., Holthuysen, A. E., van der Kraan, P. M., Roth, J., van Rooijen, N., & van den Berg, W. B. (2004). Synovial lining macrophages mediate osteophyte formation during experimental osteoarthritis. Osteoarthritis Cartilage, 12(8), 627-635. doi:10.1016/j.joca.2004.03.003

Blom, A. B., van Lent, P. L., Libregts, S., Holthuysen, A. E., van der Kraan, P. M., van Rooijen, N., & van den Berg, W. B. (2007). Crucial role of macrophages in matrix metalloproteinase-mediated cartilage destruction during experimental osteoarthritis: involvement of matrix metalloproteinase 3. Arthritis Rheum, 56(1), 147-157. doi:10.1002/art.22337

Cano, A., Leonard, M. T., & Franz, A. (2005). The significant other version of the Pain Catastrophizing Scale (PCS-S): preliminary validation. Pain, 119(1-3), 26-37. doi:10.1016/j.pain.2005.09.009

Carlesso, L. C., Niu, J., Segal, N. A., Frey-Law, L. A., Lewis, C. E., Nevitt, M. C., & Neogi, T. (2017). The Effect of Widespread Pain on Knee Pain Worsening, Incident Knee Osteoarthritis (OA), and Incident Knee Pain: The Multicenter OA (MOST) Study. J Rheumatol. doi:10.3899/jrheum.160853

Chan, C. Y., Tsang, H. H., Lau, C. S., & Chung, H. Y. (2014). Prevalence of depressive and anxiety disorders and validation of the Hospital Anxiety and Depression Scale as a screening tool in axial spondyloarthritis patients. Int J Rheum Dis. doi:10.1111/1756-185X.12456

Chibnall, J. T., & Tait, R. C. (2005). Confirmatory factor analysis of the Pain Catastrophizing Scale in African American and Caucasian Workers’ Compensation claimants with low back injuries. Pain, 113(3), 369-375. doi:10.1016/j.pain.2004.11.016

Cho, H. J., Morey, V., Kang, J. Y., Kim, K. W., & Kim, T. K. (2015). Prevalence and Risk Factors of Spine, Shoulder, Hand, Hip, and Knee Osteoarthritis in Community-dwelling Koreans Older Than Age 65 Years. Clin Orthop Relat Res, 473(10), 3307-3314. doi:10.1007/s11999-015-4450-3

Choe, J. Y., Bae, J., Jung, H. Y., Park, S. H., Lee, H. J., & Kim, S. K. (2012). Serum resistin level is associated with radiographic changes in hand osteoarthritis: cross-sectional study. Joint Bone Spine, 79(2), 160-165. doi:10.1016/j.jbspin.2011.04.009

Cooper, C., Adachi, J. D., Bardin, T., Berenbaum, F., Flamion, B., Jonsson, H., . . . Bruyère, O. (2013). How to define responders in osteoarthritis. Curr Med Res Opin, 29(6), 10.

DADOS Project, 2015. http://www.dadosproject.com/

Daghestani, H. N., Pieper, C. F., & Kraus, V. B. (2015). Soluble macrophage biomarkers indicate inflammatory phenotypes in patients with knee osteoarthritis. Arthritis Rheumatol, 67(4), 956-965. doi:10.1002/art.39006

Dahaghin, S., Bierma-Zeinstra, S. M., Ginai, A. Z., Pols, H. A., Hazes, J. M., & Koes, B. W. (2005). Prevalence and pattern of radiographic hand osteoarthritis and association with pain and disability (the Rotterdam study). Ann Rheum Dis, 64(5), 682-687. doi:10.1136/ard.2004.023564

de Lange-Brokaar, B. J., Ioan-Facsinay, A., van Osch, G. J., Zuurmond, A. M., Schoones, J., Toes, R. E., . . . Kloppenburg, M. (2012). Synovial inflammation, immune cells and their cytokines in osteoarthritis: a review. Osteoarthritis Cartilage, 20(12), 1484-1499. doi:10.1016/j.joca.2012.08.027

Dritsaki, M., Petrou, S., Williams, M., & Lamb, S. E. (2017). An empirical evaluation of the SF-12, SF-6D, EQ-5D and Michigan Hand Outcome Questionnaire in patients with rheumatoid arthritis of the hand. Health Qual Life Outcomes, 15(1), 20. doi:10.1186/s12955-016-0584-6

EuroQol, G. (1990). EuroQol–a new facility for the measurement of health-related quality of life. Health Policy, 16(3), 199-208.

Fahy, N., de Vries-van Melle, M. L., Lehmann, J., Wei, W., Grotenhuis, N., Farrell, E., . . . van Osch, G. J. (2014). Human osteoarthritic synovium impacts chondrogenic differentiation of mesenchymal stem cells via macrophage polarisation state. Osteoarthritis Cartilage, 22(8), 1167-1175. doi:10.1016/j.joca.2014.05.021

Filkova, M., Liskova, M., Hulejova, H., Haluzik, M., Gatterova, J., Pavelkova, A., . . . Senolt, L. (2009). Increased serum adiponectin levels in female patients with erosive compared with non-erosive osteoarthritis. Ann Rheum Dis, 68(2), 295-296. doi:10.1136/ard.2008.095737

Gandhi, R., Kapoor, M., Mahomed, N. N., & Perruccio, A. V. (2015). A comparison of obesity related adipokine concentrations in knee and shoulder osteoarthritis patients. Obes Res Clin Pract, 9(4), 420-423. doi:10.1016/j.orcp.2015.02.003

Gracely, R. H., Geisser, M. E., Giesecke, T., Grant, M. A., Petzke, F., Williams, D. A., & Clauw, D. J. (2004). Pain catastrophizing and neural responses to pain among persons with fibromyalgia. Brain, 127(Pt 4), 835-843. doi:10.1093/brain/awh098

Haara, M. M., Heliovaara, M., Kroger, H., Arokoski, J. P., Manninen, P., Karkkainen, A., . . . Aromaa, A. (2004). Osteoarthritis in the carpometacarpal joint of the thumb. Prevalence and associations with disability and mortality. J Bone Joint Surg Am, 86-A(7), 1452-1457.

Haugen, I. K., Englund, M., Aliabadi, P., Niu, J., Clancy, M., Kvien, T. K., & Felson, D. T. (2011). Prevalence, incidence and progression of hand osteoarthritis in the general population: the Framingham Osteoarthritis Study. Ann Rheum Dis, 70(9), 1581-1586. doi:10.1136/ard.2011.150078

Helvik, A. S., Engedal, K., Skancke, R. H., & Selbaek, G. (2011). A psychometric evaluation of the Hospital Anxiety and Depression Scale for the medically hospitalized elderly. Nord J Psychiatry, 65(5), 338-344. doi:10.3109/08039488.2011.560684

Henrotin, Y., Sanchez, C., Bay-Jensen, A. C., & Mobasheri, A. (2016). Osteoarthritis biomarkers derived from cartilage extracellular matrix: Current status and future perspectives. Ann Phys Rehabil Med, 59(3), 145-148. doi:10.1016/j.rehab.2016.03.004

Hudak, P. L., Amadio, P. C., & Bombardier, C. (1996). Development of an upper extremity outcome measure: the DASH (disabilities of the arm, shoulder and hand) [corrected]. The Upper Extremity Collaborative Group (UECG). Am J Ind Med, 29(6), 602-608. doi:10.1002/(SICI)1097-0274(199606)29:6<602::AID-AJIM4>3.0.CO;2-L

Jenkinson, C., Layte, R., Jenkinson, D., Lawrence, K., Petersen, S., Paice, C., & Stradling, J. (1997). A shorter form health survey: can the SF-12 replicate results from the SF-36 in longitudinal studies? J Public Health Med, 19(2), 179-186.

Jonsson, H., Manolescu, I., Stefansson, S. E., Ingvarsson, T., Jonsson, H. H., Manolescu, A., . . . Stefansson, K. (2003). The inheritance of hand osteoarthritis in Iceland. Arthritis Rheum, 48(2), 391-395. doi:10.1002/art.10785

Kim, C., Linsenmeyer, K. D., Vlad, S. C., Guermazi, A., Clancy, M. M., Niu, J., & Felson, D. T. (2014). Prevalence of radiographic and symptomatic hip osteoarthritis in an urban United States community: the Framingham osteoarthritis study. Arthritis Rheumatol, 66(11), 3013-3017. doi:10.1002/art.38795

Kraus, V. B., Hargrove, D. E., Hunter, D. J., Renner, J. B., & Jordan, J. M. (2017). Establishment of reference intervals for osteoarthritis-related soluble biomarkers: the FNIH/OARSI OA Biomarkers Consortium. Ann Rheum Dis, 76(1), 179-185. doi:10.1136/annrheumdis-2016-209253

Lane, N. E., Hochberg, M. C., Nevitt, M. C., Simon, L. S., Nelson, A. E., Doherty, M., . . . Flechsenhar, K. (2015). OARSI Clinical Trials Recommendations: Design and conduct of clinical trials for hip osteoarthritis. Osteoarthritis Cartilage, 23(5), 761-771. doi:10.1016/j.joca.2015.03.006

Li, Y. H., Tavallaee, G., Tokar, T., Nakamura, A., Sundararajan, K., Weston, A., . . . Kapoor, M. (2016). Identification of synovial fluid microRNA signature in knee osteoarthritis: differentiating early- and late-stage knee osteoarthritis. Osteoarthritis Cartilage, 24(9), 1577-1586. doi:10.1016/j.joca.2016.04.019

Mahler, E. A., Zweers, M. C., van Lent, P. L., Blom, A. B., van den Hoogen, F. H., van den Berg, W. B., . . . den Broeder, A. A. (2015). Association between serum levels of the proinflammatory protein S100A8/A9 and clinical and structural characteristics of patients with established knee, hip, and hand osteoarthritis. Scand J Rheumatol, 44(1), 56-60. doi:10.3109/03009742.2014.918176

Manno, R. L., Bingham, C. O., 3rd, Paternotte, S., Gossec, L., Halhol, H., Giacovelli, G., . . . Dougados, M. (2012). OARSI-OMERACT initiative: defining thresholds for symptomatic severity and structural changes in disease modifying osteoarthritis drug (DMOAD) clinical trials. Osteoarthritis Cartilage, 20(2), 93-101. doi:10.1016/j.joca.2011.11.013

Marshall, M., van der Windt, D., Nicholls, E., Myers, H., & Dziedzic, K. (2011). Radiographic thumb osteoarthritis: frequency, patterns and associations with pain and clinical assessment findings in a community-dwelling population. Rheumatology (Oxford), 50(4), 735-739. doi:10.1093/rheumatology/keq371

Massengale, M., Lu, B., Pan, J. J., Katz, J. N., & Solomon, D. H. (2012). Adipokine hormones and hand osteoarthritis: radiographic severity and pain. PLoS One, 7(10), e47860. doi:10.1371/journal.pone.0047860

Massengale, M., Reichmann, W. M., Losina, E., Solomon, D. H., & Katz, J. N. (2012). The relationship between hand osteoarthritis and serum leptin concentration in participants of the Third National Health and Nutrition Examination Survey. Arthritis Res Ther, 14(3), R132. doi:10.1186/ar3864

Mathiowetz, V., Weber, K., Volland, G., & Kashman, N. (1984). Reliability and validity of grip and pinch strength evaluations. J Hand Surg Am, 9(2), 222-226.

Melzack, R. (1975). The McGill Pain Questionnaire: major properties and scoring methods. Pain, 1(3), 277-299.

Melzack, R. (1987). The short-form McGill Pain Questionnaire. Pain, 30(2), 191-197.

Mobasheri, A., Bay-Jensen, A. C., van Spil, W. E., Larkin, J., & Levesque, M. C. (2017). Osteoarthritis Year in Review 2016: biomarkers (biochemical markers). Osteoarthritis Cartilage, 25(2), 199-208. doi:10.1016/j.joca.2016.12.016

Moriatis Wolf, J., Turkiewicz, A., Atroshi, I., & Englund, M. (2014). Prevalence of doctor-diagnosed thumb carpometacarpal joint osteoarthritis: an analysis of Swedish health care. Arthritis Care Res (Hoboken), 66(6), 961-965. doi:10.1002/acr.22250

Nakamura, A., Rampersaud, Y. R., Sharma, A., Lewis, S. J., Wu, B., Datta, P., . . . Kapoor, M. (2016). Identification of microRNA-181a-5p and microRNA-4454 as mediators of facet cartilage degeneration. JCI Insight, 1(12), e86820. doi:10.1172/jci.insight.86820

Ochi, K., Iwamoto, T., Saito, A., Ikari, K., Toyama, Y., Taniguchi, A., . . . Momohara, S. (2015). Construct validity, reliability, response rate, and association with disease activity of the quick disabilities of the arm, shoulder and hand questionnaire in the assessment of rheumatoid arthritis. Mod Rheumatol, 25(2), 241-245. doi:10.3109/14397595.2014.939420

Osman, A., Barrios, F. X., Gutierrez, P. M., Kopper, B. A., Merrifield, T., & Grittmann, L. (2000). The Pain Catastrophizing Scale: further psychometric evaluation with adult samples. J Behav Med, 23(4), 351-365.

Osman, A., Barrios, F. X., Kopper, B. A., Hauptmann, W., Jones, J., & O’Neill, E. (1997). Factor structure, reliability, and validity of the Pain Catastrophizing Scale. J Behav Med, 20(6), 589-605.

Perruccio, A. V., Power, J. D., Evans, H. M., Mahomed, S. R., Gandhi, R., Mahomed, N. N., & Davis, A. M. (2012). Multiple joint involvement in total knee replacement for osteoarthritis: Effects on patient-reported outcomes. Arthritis Care Res (Hoboken), 64(6), 838-846. doi:10.1002/acr.21629

Roux, C. H., Foltz, V., Maheu, E., Baron, G., Gandjbakhch, F., Lukas, C., . . . French Section on, O. (2016). MRI and serum biomarkers correlate with radiographic features in painful hand osteoarthritis. Clin Exp Rheumatol, 34(6), 991-998.

Sullivan, M. J., Lynch, M. E., & Clark, A. J. (2005). Dimensions of catastrophic thinking associated with pain experience and disability in patients with neuropathic pain conditions. Pain, 113(3), 310-315. doi:10.1016/j.pain.2004.11.003

Turkiewicz, A., Petersson, I. F., Bjork, J., Hawker, G., Dahlberg, L. E., Lohmander, L. S., & Englund, M. (2014). Current and future impact of osteoarthritis on health care: a population-based study with projections to year 2032. Osteoarthritis Cartilage, 22(11), 1826-1832. doi:10.1016/j.joca.2014.07.015

Van Damme, S., Crombez, G., Bijttebier, P., Goubert, L., & Van Houdenhove, B. (2002). A confirmatory factor analysis of the Pain Catastrophizing Scale: invariant factor structure across clinical and non-clinical populations. Pain, 96(3), 319-324.

Ware, J., Jr., Kosinski, M., & Keller, S. D. (1996). A 12-Item Short-Form Health Survey: construction of scales and preliminary tests of reliability and validity. Med Care, 34(3), 220-233.

Wilder, F. V., Barrett, J. P., & Farina, E. J. (2006). Joint-specific prevalence of osteoarthritis of the hand. Osteoarthritis Cartilage, 14(9), 953-957. doi:10.1016/j.joca.2006.04.013

Yusuf, E. (2012). Metabolic factors in osteoarthritis: obese people do not walk on their hands. Arthritis Res Ther, 14(4), 123. doi:10.1186/ar3894

Yusuf, E., Ioan-Facsinay, A., Bijsterbosch, J., Klein-Wieringa, I., Kwekkeboom, J., Slagboom, P. E., Kloppenburg, M. (2011). Association between leptin, adiponectin and resistin and long-term progression of hand osteoarthritis. Ann Rheum Dis, 70(7), 1282-1284. doi:10.1136/ard.2010.146282

Zigmond, A. S., & Snaith, R. P. (1983). The hospital anxiety and depression scale. Acta Psychiatr Scand, 67(6), 361-370.



Recommendation
With Our Resume Writing Help, You Will Land Your Dream Job
Resume Writing Service, Resume101
Trust your assignments to an essay writing service with the fastest delivery time and fully original content.
Essay Writing Service, EssayPro
Nowadays, the PaperHelp website is a place where you can easily find fast and effective solutions to virtually all academic needs
Universal Writing Solution, PaperHelp
Professional Custom
Professional Custom Essay Writing Services
In need of qualified essay help online or professional assistance with your research paper?
Browsing the web for a reliable custom writing service to give you a hand with college assignment?
Out of time and require quick and moreover effective support with your term paper or dissertation?