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Commentary: Ahead of the Curve |

Clinical Drug Development Using Dynamic Biomarkers to Enable Personalized Health Care in COPDCOPD Drug Development and Personalized Health Care FREE TO VIEW

Asger R. Bihlet, MSc; Morten A. Karsdal, PhD; Anne-Christine Bay-Jensen, PhD; Simon Read, MD, PhD; Jacob Hull Kristensen, MSc; Jannie Marie Bülow Sand, MSc; Diana Julie Leeming, PhD; Jeppe Ragnar Andersen, MSc; Peter Lange, MD, DMSc; Jørgen Vestbo, MD, DMSc
Author and Funding Information

From Nordic Bioscience Clinical Development (Mr Bihlet), Herlev, Denmark; Nordic Bioscience (Drs Karsdal, Bay-Jensen, and Leeming; Messrs Kristensen and Andersen; and Ms Sand), Herlev, Denmark; Grünenthal (Dr Read), Aachen, Germany; Section of Respiratory Medicine (Dr Lange), Hvidovre Hospital and Institute of Public Health, Copenhagen University, Copenhagen, Denmark; and Respiratory and Allergy Research Group (Dr Vestbo), Manchester Academic Science Centre, University Hospital South Manchester NHS Foundation Trust, Manchester, England.

CORRESPONDENCE TO: Asger R. Bihlet, MSc, Nordic Bioscience, Herlev Hovedgade 207, DK-2730 Herlev, Denmark; e-mail: abi@nordicbioscience.com


Reproduction of this article is prohibited without written permission from the American College of Chest Physicians. See online for more details.


Chest. 2015;148(1):16-23. doi:10.1378/chest.15-0296
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Despite massive investments in the development of novel treatments for heterogeneous diseases such as COPD, the resources spent have only benefited a fraction of the population treated. Personalized health care to guide selection of a suitable patient population already in the clinical development of new compounds could offer a solution. This review discusses past successes and failures in drug development and biomarker research in COPD, describes research in COPD phenotypes and the required characteristics of a suitable biomarker for identifying patients at higher risk of progression, and examines the role of extracellular matrix proteins found to be upregulated in COPD. Novel biomarkers of connective tissue remodeling that may provide added value for a personalized approach by detecting subgroups of patients with active disease suitable for pharmacologic intervention are discussed.

Figures in this Article

Although clinical development of novel therapies is becoming increasingly complex, few successful attempts have been made to implement a personalized health-care (PHC) approach. An improved probability of technical success is an ambition of everyone involved in drug development, and a PHC approach theoretically would allow for selection of an appropriate patient population with a higher likelihood of success. This contrasts a largely unselected group, which in most diseases is likely to comprise various subgroups with different pathologic processes and levels of activity.1 The completion of the Human Genome Project in 20012 led to the belief that the genomic approach to PHC could enable stratification of patients according to individual genomes. However, it is now clear that this approach is not yet mature for universal implementation. Therapeutic areas for which a PHC approach in clinical research could be a significant advantage are areas characterized by high heterogeneity, such as COPD, and areas where current treatment options capable of changing the progression of the disease have demonstrated low efficacy. A recent review of AstraZeneca’s drug development failures during the period from 2005 to 2010 highlighted that projects in which biomarker-driven selection of a patient population is used in early clinical trials have a notably higher chance of success.3 As a result of these shortcomings, we are faced with the following challenges:

  • • Clinical trials with promising agents may fail to demonstrate a clinically meaningful benefit due to lack of patient selection.4

  • • If the incremental benefit from new agents is expected to be small in an unselected population, much higher patient numbers are needed to demonstrate statistically significant superiority compared with standard of care.5

  • • Higher recruitment numbers rapidly increase costs of clinical trial programs and may deter drug developers from taking potentially innovative risks.5

  • • Certain standard efficacy end points are flawed by lack of sensitivity to change and high variability, requiring high patient numbers to demonstrate significant differences.6

The concept of using biomarkers for patient selection and to monitor efficacy of the intervention in clinical research may assist in reducing the impact of these challenges. A combination of current knowledge on genetic risk factors with promising serologic biomarkers quantifying tissue- and pathology-specific changes may increase the chances of providing an earlier proof of therapeutic concept by the use of biomarker-based surrogate end points. Ideally, this could provide a faster selection of patients for new treatment options while sparing expected nonresponders the risks of adverse reactions.

The US Food and Drug Administration released a position paper to underline its commitment and investment in promoting and improving current PHC.7 According to the Food and Drug Administration, this approach should ideally be implemented before a marketing authorization is granted (ie, in clinical research).7 Disease areas in which this approach has been successful and has led to advances in treatment options share some similarities, but these seem to exclude an important group of diseases.

Diseases treated according to genotype like certain malignancies, such as various mutations in non-small cell lung cancer,8 and the use of ivacaftor for the treatment of cystic fibrosis in patients with a G551D mutation9 can be considered success stories. Yet, the correspondence between genotype and treatment may be less obvious for chronic diseases particularly associated with environmental exposures, choice of lifestyle, and, to a much lesser degree, genetic predisposition. From a PHC perspective, these disease areas may share the disadvantage of not arising as a consequence of a single genetic anomaly, but to a higher degree, they are driven by exogenous factors continuously exerting a detrimental effect on a given tissue. It should be considered instead whether these patients would experience an additional benefit from an approach that reflects either an important element in or the end product of the pathologic biochemical changes caused by the disease process, which may not be caused by one or few genetic drivers. However, the unknown factor in this equation is which biomarkers would be suitable to improve chances of success in these disease areas, and it may be speculated that a new approach should focus on the detection of such markers.

COPD is a therapeutic area in which previous attempts to develop new disease-modifying treatments have conferred limited success.6 Being considered a lifestyle disease, the approach to tailor treatment could prove particularly useful in COPD clinical research given that an appropriate marker of disease activity could be available for phenotyping.

The pathogenesis of COPD is predominantly driven by cigarette smoking and environmental exposures, such as biomass exposure.10 Although significant efforts have been invested in identifying genetic factors influencing either pathogenesis or disease severity, only a very small proportion of patients with COPD seem to carry identifiable genetic components, such as severe α1-antitrypsin deficiency, known to significantly influence the development of emphysema.11 The range of treatment options affecting disease progression in COPD is limited.6 The phenotyping is mainly based on a combination of clinical and morphologic features, such as type and severity of symptoms (eg, presence or absence of chronic bronchitis), frequency of exacerbations (frequent-exacerbator phenotype), presence of emphysema on high-resolution CT scan, and presence of asthmatic features in addition to chronic airflow limitation (asthma-COPD overlap syndrome).12,13

Results from the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) study suggest that a frequent-exacerbator phenotype exists, irrespective of disease severity, and that the best predictor of future exacerbations is a history of exacerbations.14 Hurst et al14 and Langsetmo et al15 also discussed the possible variability in patient-reported events because the patient may not recognize symptoms as an exacerbation and, thus, not report them. Imaging assessments of the lung parenchyma and airways using CT scan is feasible.16 Elevated levels of inflammatory markers in blood also could predict groups with a higher risk of future exacerbations,17 but none of these modalities has been approved for standard clinical care for individual patients. COPD is largely an inflammatory airway disease, and although treatment with the antiinflammatory phosphodiesterase-4 inhibitor roflumilast in a clinical trial of patients with severe COPD demonstrated a modest increase in FEV1, it did not significantly lower the rate of moderate to severe exacerbations compared with placebo in the total population studied.18 Yet in the same trial, a subgroup analysis of the patients with severe or very severe COPD (GOLD [Global Initiative for Chronic Obstructive Lung Disease] III and IV) with presence of chronic bronchitis showed a statistically significant reduction in exacerbations, indicating that these patients could benefit more from treatment than the otherwise unselected population with severe COPD.18,19 Particularly noteworthy are the very modest overall declines seen in prebronchodilator FEV1 for the placebo groups of the trials comparing roflumilast to placebo (−9 mL/y), indicating that the disease generally progressed slowly.20 This finding is also reflected in the ECLIPSE observational study in which Vestbo et al21 reported an average annual FEV1 decline of 33 mL and noted that a significant proportion of patients did not progress at all. Data from several large-scale clinical trials (summarized in Table 1) have indicated that the numerical decline in lung function is higher in the earlier stages (GOLD II) of disease than in the later stages (GOLD III and IV).2225 This observation may be related to the frequency of smoking cessation being highest among patients with the most severe disease but could also suggest that the COPD population comprises subgroups with various FEV1 trajectories. In particular, some patients with COPD may never have experienced a significant decline in FEV1 but simply had a low maximally attained lung function in early adulthood, thereby increasing their likelihood of having significant airflow limitation despite a normal or only slightly increased decline.28,29 Thus, the challenge is early selection of the patients progressing fast. This phenomenon and a proposed new approach in trial design are exemplified in Figure 1.

Table Graphic Jump Location
TABLE 1 ]  Overview of Yearly Decline in FEV1 in COPD Trials

ECLIPSE = Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints; GOLD = Global Initiative for Chronic Obstructive Lung Disease; M2-124 = Effect of Roflumilast on Exacerbation Rate in Patients With COPD. The AURA Study; M2-125 = Effect of Roflumilast on Exacerbation Rate in Patients With COPD. The HERMES Study; N/A = not available; TORCH = Towards a Revolution in COPD Health; UPLIFT = Understanding Potential Long-term Impacts on Function with Tiotropium.

a 

Defined as GOLD II (baseline FEV1 ≥ 50% predicted).

b 

Defined as GOLD IV (baseline FEV1 < 30% predicted).

c 

At y 3 from trial initiation.

Figure Jump LinkFigure 1 –  Simplistic depiction of disease progression in a hypothesized patient with COPD experiencing a rapid decline in FEV1 in the initial stages of the disease followed by slowly progressing disease. The length of Boxes 1a and 1b indicate time needed to demonstrate statistically significant differences in FEV1. Contemporary clinical trials in COPD18,20 (Box 1a) recruit patients with moderate to severe symptoms at a late stage of disease, in which the period the disease progresses slowly or not at all.2225 This renders a poor possibility to demonstrate disease modification by medical intervention. In contrast, if patients had been in the trial during the period in which the FEV1 declined at a significantly higher rate, less time and fewer patients would be needed to demonstrate a difference between an efficacious treatment and placebo (Box 1b). Suitable biomarkers reflecting disease activity could indicate an impact on disease progression before significant clinical manifestations occur, and selection of patients based on a high-risk biomarker profile may reduce the duration of the clinical trial.Grahic Jump Location

In Figure 2,30 three presently well-recognized COPD phenotypes are illustrated.13 COPD is a heterogeneous disease that shows different clinical and radiologic features even within these three phenotypes; thus, an even more accurate phenotyping is needed. High-quality phenotyping by, for example, a biomarker may provide a highly welcomed tool for patient differentiation and selection for COPD clinical trials to optimize the number of expected responders to therapy in order to move from a stochastic treatment strategy (Fig 2A) to a more targeted patient selection approach (Fig 2B). Together, these findings indicate an important difference between disease severity assessed by GOLD and disease activity (as exemplified in Fig 331) and underline the need for dynamic biomarkers reflecting the disease activity of COPD.

Figure Jump LinkFigure 2 –  A and B, Depiction of three proposed COPD phenotypes in the random treatment strategy (A) and in a targeted patient selection approach (B). The total COPD population comprises numerous phenotypes that either have been identified or remain to be characterized. Here, three known phenotypes of COPD are illustrated: frequent exacerbator, emphysema hyperinflation; and COPD-asthma overlap. However, better and more-specific phenotyping is needed.13 Each phenotype at an early time point will likely respond differently to therapies of various modes of action (A). With the example of a PDE4 inhibitor such as roflumilast, treatment of all patients regardless of phenotype could lead to a suboptimal response.20 Patient selection using a personalized health-care approach will lead to increased response rates if the treatment mode of action is paired with a selected phenotype with a greater potential for response (as in the case of roflumilast) in the frequent exacerbator phenotype (B).19 PDE4 = phosphodiesterase-4. (Adapted with permission from Karsdal et al.30)Grahic Jump Location
Figure Jump LinkFigure 3 –  Biomarker of disease activity vs disease severity. Disease progression may occur in stages followed by periods of inertia.31 A biomarker of disease activity reflects the disease activity at the time it is measured but not disease severity, whereas a diagnostic biomarker may reflect disease severity but not disease activity. As a tool for predicting progression, a biomarker of disease activity is more suitable than a biomarker that solely reflects the current disease state.Grahic Jump Location

Although a series of biomarkers have been shown to be significantly associated with mortality in the ECLIPSE study, only the biomarker club cell secretory protein-16 at baseline predicted a rapid FEV1 decline with a modest effect size of 4 ± 2 mL per year per SD. Plasma fibrinogen was found to be correlated with exacerbation rate; BMI, airflow obstruction, dyspnea, and exercise capacity (BODE) index; and mortality.21,26,32 Consequently, more-suitable biomarkers reflecting disease activity and, thereby, a capability of identifying patients with particularly progressive COPD are needed.33 The assessment of plasma proadrenomedullin levels in the Predicting Outcome Using Systemic Markers in Severe Exacerbations of Chronic Obstructive Pulmonary Disease (PROMISE-COPD) study indicated that biochemical markers can improve traditional mortality indexes.34 In this case, proadrenomedullin plasma levels plus BODE index predicted mortality in patients with COPD better than BODE index alone.34 Progression of COPD involves pathologic remodeling and destruction of the extracellular matrix (ECM), especially in the small airways during early chronic bronchitis. Thus, new techniques to quantify the ECM lung tissue destruction during chronic inflammation and fibrosis could be promising biomarkers of disease activity in respiratory conditions, and if further validated, they could ideally be used for the phenotyping of patients with COPD and as surrogate end points.35,36

The significant research efforts invested in discovering suitable biomarkers for COPD have resulted in very little change in current treatment and research paradigms.23,25,37,38 Besides a lack of efficacy of the agents studied, elements such as suboptimal end points, study design, and inclusion of an unselected patient population may contribute to a lack of demonstrated benefit, as seen in many ambitious and promising drug development projects that failed in early stage development.6,39 The lack of measurable benefit may partly be caused by a lack of adequately suitable surrogate end points. One class of biomarkers, disease activity markers for prognostic and efficacy of intervention measures, is of particular relevance regarding surrogate end points.40

Efforts to identify genomic biomarkers associated with progression of COPD have yielded limited clinical utility.11 Furthermore, genetic biomarkers exhibit limited dynamic capabilities in that they cannot change as a response to intervention and, thus, are inadequate for monitoring intervention efficacy. However, serologic biomarkers capable of reflecting dynamic changes in a pathologic state hold promise in this area.

ECM remodeling is a delicate equilibrium and a prerequisite for maintenance of a healthy tissue in which old proteins are continuously degraded and new proteins are formed.40 This delicate balance is disturbed in connective tissue diseases, resulting in an increased turnover of both formation and degradation in the peripheral airway wall, leading to tissue disruption and fibrosis.41,42 COPD is, to a large extent, a connective tissue disease that may, in part, be described as an uncontrolled damage-repair process resulting from chronic inflammation. This leads to an imbalanced tissue turnover, accumulation of ECM proteins,34 and altered tissue remodeling, which finally results in loss of tissue function and, eventually, organ failure. It has been proposed that persistent injury to the lung epithelium drives a process known as the epithelial-to-mesenchymal transition in which transforming growth factor-β overexpression directs epithelial cell transdifferentiation into a mesenchymal cell and then to a myofibroblast during lung wound healing.41,43 Epithelial-to-mesenchymal transition is believed to be a key factor during airway remodeling and fibrosis development; however, resident fibroblasts, α-smooth muscle cells, and fibrocytes are also reported to differentiate into myofibroblasts during the process. Myofibroblasts are able to produce and deposit ECM proteins, especially collagens, as well as regulate the tissue turnover balance by secretion of matrix metalloproteinases (MMPs).41,43 It has been demonstrated in patients with COPD that the airway wall composition is changed compared with healthy individuals, resulting in increased deposition of collagens type I and III; fibronectin; laminin44,45; and the proteoglycans versican, biglycan, decorin, and perlecan,46 all of which allegedly have severe effects on lung integrity and ability to recoil. A subset of pathologic proteases has been reported to be overexpressed in COPD-affected tissue, such as elastase47 and MMP-1, -2, -7, and -12,48 most of which possess collagenolytic activity. This results in the release of protease-specific fragments of such signature proteins. It is well recognized that in emphysema, in addition to degradation of elastin in alveoli, collagens are degraded,45 thus generating elastin and collagen fragments expected to be released into systemic circulation.

These protease-derived small protein fragments may be used as serologic biomarkers of tissue degradation or formation, thus reflecting the remodeling activity.33,49,50 These fragments may be used as early diagnostic or prognostic serologic biomarkers. Examples of biomarkers of structural proteins are MMP-2-, -9-, and -13-mediated destruction of interstitial collagen types I, III, V, and VI5153 as well as the basement membrane type IV collagen,54 which all have been associated with connective tissue disease. The generation of tissue-specific biomarkers of disease activity is illustrated in Figure 4. These end products of tissue destruction may be considered as the convergence of signals from many different pathways.

Figure Jump LinkFigure 4 –  A number of growth factors and cytokines are produced in the development of a disease such as COPD. Each factor may trigger different intracellular signaling pathways that lead to the secretion of proteases and protease inhibitors as well as the synthesis of various extracellular proteins. Newly formed procollagens are incorporated into the extracellular matrix, and their propeptides are removed to form the mature collagen molecule. The secreted proteases will degrade the existing extracellular matrix components, releasing various protein fragments (neoepitopes) into circulation. (Adapted with permission from Karsdal et al.49)Grahic Jump Location

Enzyme-linked immunosorbent assays measuring circulating fragments resulting from cleavage of proteins of the ECM (neoepitopes) have been developed.35,51,55 Neoepitope fragments of collagen types II and III generated by MMPs C2M and C3M, respectively, have been shown to reflect disease activity in rheumatoid arthritis and on this basis, to predict response to anti-IL-6 treatment with tocilizumab in a retrospective analysis of the Tocilizumab Safety and the Prevention of Structural Joint Damage (LITHE) study.56 Related markers such as MMP-generated neoepitopes of collagen types I (C1M51) and VI (C6M57) and biglycan (BGM58) have recently been discussed in the literature as appropriate markers for disease activity in interstitial lung disease, particularly idiopathic pulmonary fibrosis.36

In the future, such information may be obtained for patients with COPD through appropriate biomarkers such as lung tissue-specific neoepitope markers reflecting disease activity. This would enable a more-focused and shorter proof-of-concept trial with fewer patients as illustrated in Figure 1, thus assisting in innovative drug development.

Although many advances have been made in identifying biomarkers suitable for PHC and patient selection for COPD clinical trials, the current application of these findings is scarce. Nongenomic biomarkers that reflect disease activity may provide the ability to monitor treatment effect prior to the clinical manifestations of disease and perhaps in combination with genomic markers be used for selection of high-risk study populations. Phenotypic selection of patients with fast disease progression for clinical trials can increase the chance of demonstrating a significant treatment effect as well as reduce trial duration. This would be a significant advantage compared with conventional drug development strategies, benefiting patients, physicians, and society.

Financial/nonfinancial disclosures: The authors have reported to CHEST the following conflicts of interest: Messrs Bihlet, Kristensen, and Andersen; Drs Karsdal, Bay-Jensen, and Leeming; and Ms Sand are full-time employees of Nordic Bioscience, a company engaged in the discovery and development of biochemical markers. The protein fragment biomarkers of the extracellular matrix C1M, C2M, C3M, C6M, and BGM discussed in this review are being developed by Nordic Bioscience with the aim of regulatory approval and the purpose of obtaining scientific knowledge of extracellular matrix remodeling in given tissues, pathologic or not. None of the aforementioned biomarkers are currently commercially available for purposes other than research. Messrs Bihlet and Andersen and Drs Karsdal and Bay-Jensen own shares in Nordic Bioscience. Dr Read is a full-time employee of Grünenthal. Dr Vestbo has received honoraria for advising and presenting from Almirall SA, AstraZeneca, Boehringer Ingelheim GmbH, Chiesi Farmaceutici SpA, GlaxoSmithKline plc, and Novartis AG. Dr Lange has reported that no potential conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.

BODE

BMI, airflow obstruction, dyspnea, and exercise

ECLIPSE

Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints

ECM

extracellular matrix

GOLD

Global Initiative for Chronic Obstructive Lung Disease

MMP

matrix metalloproteinase

PHC

personalized health care

Karsdal MA, Henriksen K, Leeming DJ, et al. Biochemical markers and the FDA critical path: how biomarkers may contribute to the understanding of pathophysiology and provide unique and necessary tools for drug development. Biomarkers. 2009;14(3):181-202. [CrossRef] [PubMed]
 
Lander ES, Linton LM, Birren B, et al; International Human Genome Sequencing Consortium. Initial sequencing and analysis of the human genome [published correction appears in Nature. 2001;411(6838):720]. Nature. 2001;409(6822):860-921. [CrossRef] [PubMed]
 
Cook D, Brown D, Alexander R, et al. Lessons learned from the fate of AstraZeneca’s drug pipeline: a five-dimensional framework. Nat Rev Drug Discov. 2014;13(6):419-431. [CrossRef] [PubMed]
 
Sacks LV, Shamsuddin HH, Yasinskaya YI, Bouri K, Lanthier ML, Sherman RE. Scientific and regulatory reasons for delay and denial of FDA approval of initial applications for new drugs, 2000-2012. JAMA. 2014;311(4):378-384. [CrossRef] [PubMed]
 
Scannell JW, Blanckley A, Boldon H, Warrington B. Diagnosing the decline in pharmaceutical R&D efficiency. Nat Rev Drug Discov. 2012;11(3):191-200. [CrossRef] [PubMed]
 
Calverley PM. New treatments for COPD: many miles still to go. Lancet Respir Med. 2014;2(1):6-7. [CrossRef] [PubMed]
 
 Paving the Way for Personalized Medicine: FDA’s Role in a New Era of Medical Product Development. Rockville, MD: US Food and Drug Administration; 2013.
 
Forde PM, Ettinger DS. Targeted therapy for non-small-cell lung cancer: past, present and future. Expert Rev Anticancer Ther. 2013;13(6):745-758. [CrossRef] [PubMed]
 
Accurso FJ, Rowe SM, Clancy JP, et al. Effect of VX-770 in persons with cystic fibrosis and the G551D-CFTR mutation. N Engl J Med. 2010;363(21):1991-2003. [CrossRef] [PubMed]
 
Burney P, Jithoo A, Kato B, et al; Burden of Obstructive Lung Disease (BOLD) Study. Chronic obstructive pulmonary disease mortality and prevalence: the associations with smoking and poverty–a BOLD analysis. Thorax. 2014;69(5):465-473. [CrossRef] [PubMed]
 
Smolonska J, Wijmenga C, Postma DS, Boezen HM. Meta-analyses on suspected chronic obstructive pulmonary disease genes: a summary of 20 years’ research. Am J Respir Crit Care Med. 2009;180(7):618-631. [CrossRef] [PubMed]
 
Vestbo J, Hurd SS, Agustí AG, et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. Am J Respir Crit Care Med. 2013;187(4):347-365. [CrossRef] [PubMed]
 
Segreti A, Stirpe E, Rogliani P, Cazzola M. Defining phenotypes in COPD: an aid to personalized healthcare. Mol Diagn Ther. 2014;18(4):381-388. [CrossRef] [PubMed]
 
Hurst JR, Vestbo J, Anzueto A, et al; Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) Investigators. Susceptibility to exacerbation in chronic obstructive pulmonary disease. N Engl J Med. 2010;363(12):1128-1138. [CrossRef] [PubMed]
 
Langsetmo L, Platt RW, Ernst P, Bourbeau J. Underreporting exacerbation of chronic obstructive pulmonary disease in a longitudinal cohort. Am J Respir Crit Care Med. 2008;177(4):396-401. [CrossRef] [PubMed]
 
Madani A, Zanen J, de Maertelaer V, Gevenois PA. Pulmonary emphysema: objective quantification at multi-detector row CT—comparison with macroscopic and microscopic morphometry. Radiology. 2006;238(3):1036-1043. [CrossRef] [PubMed]
 
Thomsen M, Ingebrigtsen TS, Marott JL, et al. Inflammatory biomarkers and exacerbations in chronic obstructive pulmonary disease. JAMA. 2013;309(22):2353-2361. [CrossRef] [PubMed]
 
Calverley PM, Sanchez-Toril F, McIvor A, Teichmann P, Bredenbroeker D, Fabbri LM. Effect of 1-year treatment with roflumilast in severe chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2007;176(2):154-161. [CrossRef] [PubMed]
 
Wedzicha JA, Rabe KF, Martinez FJ, et al. Efficacy of roflumilast in the COPD frequent exacerbator phenotype. Chest. 2013;143(5):1302-1311. [CrossRef] [PubMed]
 
Calverley PM, Rabe KF, Goehring UM, Kristiansen S, Fabbri LM, Martinez FJ; M2-124 and M2-125 Study Groups. Roflumilast in symptomatic chronic obstructive pulmonary disease: two randomised clinical trials. Lancet. 2009;374(9691):685-694. [CrossRef] [PubMed]
 
Vestbo J, Agusti A, Wouters EF, et al; Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints Study Investigators. Should we view chronic obstructive pulmonary disease differently after ECLIPSE? A clinical perspective from the study team. Am J Respir Crit Care Med. 2014;189(9):1022-1030. [CrossRef] [PubMed]
 
Decramer M, Celli B, Kesten S, Lystig T, Mehra S, Tashkin DP; UPLIFT Investigators. Effect of tiotropium on outcomes in patients with moderate chronic obstructive pulmonary disease (UPLIFT): a prespecified subgroup analysis of a randomised controlled trial. Lancet. 2009;374(9696):1171-1178. [CrossRef] [PubMed]
 
Calverley PM, Anderson JA, Celli B, et al; TORCH Investigators. Salmeterol and fluticasone propionate and survival in chronic obstructive pulmonary disease. N Engl J Med. 2007;356(8):775-789. [CrossRef] [PubMed]
 
Celli BR, Thomas NE, Anderson JA, et al. Effect of pharmacotherapy on rate of decline of lung function in chronic obstructive pulmonary disease: results from the TORCH study. Am J Respir Crit Care Med. 2008;178(4):332-338. [CrossRef] [PubMed]
 
Tashkin DP, Celli B, Senn S, et al; UPLIFT Study Investigators. A 4-year trial of tiotropium in chronic obstructive pulmonary disease. N Engl J Med. 2008;359(15):1543-1554. [CrossRef] [PubMed]
 
Vestbo J, Edwards LD, Scanlon PD, et al; ECLIPSE Investigators. Changes in forced expiratory volume in 1 second over time in COPD. N Engl J Med. 2011;365(13):1184-1192. [CrossRef] [PubMed]
 
Jenkins CR, Jones PW, Calverley PM, et al. Efficacy of salmeterol/fluticasone propionate by GOLD stage of chronic obstructive pulmonary disease: analysis from the randomised, placebo-controlled TORCH study. Respir Res. 2009;10:59. [CrossRef] [PubMed]
 
Fletcher C, Peto R, Tinker CM, et al. The Natural History of Chronic Bronchitis and Emphysema. New York, NY: Oxford University Press; 1976.
 
Svanes C, Sunyer J, Plana E, et al. Early life origins of chronic obstructive pulmonary disease. Thorax. 2010;65(1):14-20. [CrossRef] [PubMed]
 
Karsdal MA, Christiansen C, Ladel C, Henriksen K, Kraus VB, Bay-Jensen AC. Osteoarthritis—a case for personalized health care? Osteoarthritis Cartilage. 2014;22(1):7-16. [CrossRef] [PubMed]
 
Felson D, Niu J, Sack B, Aliabadi P, McCullough C, Nevitt MC. Progression of osteoarthritis as a state of inertia. Ann Rheum Dis. 2013;72(6):924-929. [CrossRef] [PubMed]
 
Vestbo J, Anderson W, Coxson HO, et al; ECLIPSE Investigators. Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points (ECLIPSE). Eur Respir J. 2008;31(4):869-873. [CrossRef] [PubMed]
 
Vestbo J, Rennard S. Chronic obstructive pulmonary disease biomarker(s) for disease activity needed—urgently. Am J Respir Crit Care Med. 2010;182(7):863-864. [CrossRef] [PubMed]
 
Stolz D, Kostikas K, Blasi F, et al. Adrenomedullin refines mortality prediction by the BODE index in COPD: the “BODE-A” index. Eur Respir J. 2014;43(2):397-408. [CrossRef] [PubMed]
 
Leeming DJ, Sand JM, Nielsen MJ, et al. Serological investigation of the collagen degradation profile of patients with chronic obstructive pulmonary disease or idiopathic pulmonary fibrosis. Biomark Insights. 2012;7:119-126. [CrossRef] [PubMed]
 
Kristensen JH, Karsdal MA, Genovese F, et al. The role of extracellular matrix quality in pulmonary fibrosis. Respiration. 2014;88(6):487-499. [CrossRef] [PubMed]
 
Wedzicha JA, Calverley PM, Seemungal TA, Hagan G, Ansari Z, Stockley RA; INSPIRE Investigators. The prevention of chronic obstructive pulmonary disease exacerbations by salmeterol/fluticasone propionate or tiotropium bromide. Am J Respir Crit Care Med. 2008;177(1):19-26. [CrossRef] [PubMed]
 
Mushtaq Y. The COPD pipeline. Nat Rev Drug Discov. 2014;13(4):253. [CrossRef] [PubMed]
 
Watz H, Barnacle H, Hartley BF, Chan R. Efficacy and safety of the p38 MAPK inhibitor losmapimod for patients with chronic obstructive pulmonary disease: a randomised, double-blind, placebo-controlled trial. Lancet Respir Med. 2014;2(1):63-72. [CrossRef] [PubMed]
 
Karsdal MA, Krarup H, Sand JM, et al. Review article: the efficacy of biomarkers in chronic fibroproliferative diseases - early diagnosis and prognosis, with liver fibrosis as an exemplar. Aliment Pharmacol Ther. 2014;40(3):233-249. [CrossRef] [PubMed]
 
Salazar LM, Herrera AM. Fibrotic response of tissue remodeling in COPD. Lung. 2011;189(2):101-109. [CrossRef] [PubMed]
 
Karsdal MA, Nielsen MJ, Sand JM, et al. Extracellular matrix remodeling: the common denominator in connective tissue diseases. Possibilities for evaluation and current understanding of the matrix as more than a passive architecture, but a key player in tissue failure. Assay Drug Dev Technol. 2013;11(2):70-92. [CrossRef] [PubMed]
 
Crosby LM, Waters CM. Epithelial repair mechanisms in the lung. Am J Physiol Lung Cell Mol Physiol. 2010;298(6):L715-L731. [CrossRef] [PubMed]
 
Kranenburg AR, Willems-Widyastuti A, Moori WJ, et al. Enhanced bronchial expression of extracellular matrix proteins in chronic obstructive pulmonary disease. Am J Clin Pathol. 2006;126(5):725-735. [CrossRef] [PubMed]
 
Finlay GA, O’Driscoll LR, Russell KJ, et al. Matrix metalloproteinase expression and production by alveolar macrophages in emphysema. Am J Respir Crit Care Med. 1997;156(1):240-247. [CrossRef] [PubMed]
 
Hallgren O, Nihlberg K, Dahlbäck M, et al. Altered fibroblast proteoglycan production in COPD. Respir Res. 2010;11:55. [CrossRef] [PubMed]
 
Sandhaus RA, Turino G. Neutrophil elastase-mediated lung disease. COPD. 2013;10(suppl 1):60-63. [CrossRef] [PubMed]
 
Churg A, Zhou S, Wright JL. Series “matrix metalloproteinases in lung health and disease”: matrix metalloproteinases in COPD. Eur Respir J. 2012;39(1):197-209. [CrossRef] [PubMed]
 
Karsdal MA, Bay-Jensen AC, Leeming DJ, Henriksen K, Christiansen C. Quantification of “end products” of tissue destruction in inflammation may reflect convergence of cytokine and signaling pathways—implications for modern clinical chemistry. Biomarkers. 2013;18(5):375-378. [CrossRef] [PubMed]
 
Skjøt-Arkil H, Clausen RE, Nguyen QH, et al. Measurement of MMP-9 and -12 degraded elastin (ELM) provides unique information on lung tissue degradation. BMC Pulm Med. 2012;12(1):34. [CrossRef] [PubMed]
 
Leeming Dj, He Y, Veidal S, et al. A novel marker for assessment of liver matrix remodeling: an enzyme-linked immunosorbent assay (ELISA) detecting a MMP generated type I collagen neo-epitope (C1M). Biomarkers. 2011;16(7):616-628. [CrossRef] [PubMed]
 
Segovia-Silvestre T, Reichenbach V, Fernández-Varo G, et al. Circulating CO3-610, a degradation product of collagen III, closely reflects liver collagen and portal pressure in rats with fibrosis. Fibrogenesis Tissue Repair. 2011;4:19. [CrossRef] [PubMed]
 
Veidal SS, Larsen DV, Chen X, et al. MMP mediated type V collagen degradation (C5M) is elevated in ankylosing spondylitis. Clin Biochem. 2012;45(7-8):541-546. [CrossRef] [PubMed]
 
Veidal SS, Karsdal MA, Nawrocki A, et al. Assessment of proteolytic degradation of the basement membrane: a fragment of type IV collagen as a biochemical marker for liver fibrosis. Fibrogenesis Tissue Repair. 2011;4(1):22. [CrossRef] [PubMed]
 
Bay-Jensen AC, Liu Q, Byrjalsen I, et al. Enzyme-linked immunosorbent assay (ELISAs) for metalloproteinase derived type II collagen neoepitope, CIIM—increased serum CIIM in subjects with severe radiographic osteoarthritis. Clin Biochem. 2011;44(5-6):423-429. [CrossRef] [PubMed]
 
Bay-Jensen AC, Platt A, Byrjalsen I, Vergnoud P, Christiansen C, Karsdal MA. Effect of tocilizumab combined with methotrexate on circulating biomarkers of synovium, cartilage, and bone in the LITHE study. Semin Arthritis Rheum. 2014;43(4):470-478. [CrossRef] [PubMed]
 
Veidal SS, Karsdal MA, Vassiliadis E, et al. MMP mediated degradation of type VI collagen is highly associated with liver fibrosis—identification and validation of a novel biochemical marker assay. PLoS One. 2011;6(9):e24753. [CrossRef] [PubMed]
 
Genovese F, Barascuk N, Larsen L, et al. Biglycan fragmentation in pathologies associated with extracellular matrix remodeling by matrix metalloproteinases. Fibrogenesis Tissue Repair. 2013;6(1):9. [CrossRef] [PubMed]
 

Figures

Figure Jump LinkFigure 1 –  Simplistic depiction of disease progression in a hypothesized patient with COPD experiencing a rapid decline in FEV1 in the initial stages of the disease followed by slowly progressing disease. The length of Boxes 1a and 1b indicate time needed to demonstrate statistically significant differences in FEV1. Contemporary clinical trials in COPD18,20 (Box 1a) recruit patients with moderate to severe symptoms at a late stage of disease, in which the period the disease progresses slowly or not at all.2225 This renders a poor possibility to demonstrate disease modification by medical intervention. In contrast, if patients had been in the trial during the period in which the FEV1 declined at a significantly higher rate, less time and fewer patients would be needed to demonstrate a difference between an efficacious treatment and placebo (Box 1b). Suitable biomarkers reflecting disease activity could indicate an impact on disease progression before significant clinical manifestations occur, and selection of patients based on a high-risk biomarker profile may reduce the duration of the clinical trial.Grahic Jump Location
Figure Jump LinkFigure 2 –  A and B, Depiction of three proposed COPD phenotypes in the random treatment strategy (A) and in a targeted patient selection approach (B). The total COPD population comprises numerous phenotypes that either have been identified or remain to be characterized. Here, three known phenotypes of COPD are illustrated: frequent exacerbator, emphysema hyperinflation; and COPD-asthma overlap. However, better and more-specific phenotyping is needed.13 Each phenotype at an early time point will likely respond differently to therapies of various modes of action (A). With the example of a PDE4 inhibitor such as roflumilast, treatment of all patients regardless of phenotype could lead to a suboptimal response.20 Patient selection using a personalized health-care approach will lead to increased response rates if the treatment mode of action is paired with a selected phenotype with a greater potential for response (as in the case of roflumilast) in the frequent exacerbator phenotype (B).19 PDE4 = phosphodiesterase-4. (Adapted with permission from Karsdal et al.30)Grahic Jump Location
Figure Jump LinkFigure 3 –  Biomarker of disease activity vs disease severity. Disease progression may occur in stages followed by periods of inertia.31 A biomarker of disease activity reflects the disease activity at the time it is measured but not disease severity, whereas a diagnostic biomarker may reflect disease severity but not disease activity. As a tool for predicting progression, a biomarker of disease activity is more suitable than a biomarker that solely reflects the current disease state.Grahic Jump Location
Figure Jump LinkFigure 4 –  A number of growth factors and cytokines are produced in the development of a disease such as COPD. Each factor may trigger different intracellular signaling pathways that lead to the secretion of proteases and protease inhibitors as well as the synthesis of various extracellular proteins. Newly formed procollagens are incorporated into the extracellular matrix, and their propeptides are removed to form the mature collagen molecule. The secreted proteases will degrade the existing extracellular matrix components, releasing various protein fragments (neoepitopes) into circulation. (Adapted with permission from Karsdal et al.49)Grahic Jump Location

Tables

Table Graphic Jump Location
TABLE 1 ]  Overview of Yearly Decline in FEV1 in COPD Trials

ECLIPSE = Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints; GOLD = Global Initiative for Chronic Obstructive Lung Disease; M2-124 = Effect of Roflumilast on Exacerbation Rate in Patients With COPD. The AURA Study; M2-125 = Effect of Roflumilast on Exacerbation Rate in Patients With COPD. The HERMES Study; N/A = not available; TORCH = Towards a Revolution in COPD Health; UPLIFT = Understanding Potential Long-term Impacts on Function with Tiotropium.

a 

Defined as GOLD II (baseline FEV1 ≥ 50% predicted).

b 

Defined as GOLD IV (baseline FEV1 < 30% predicted).

c 

At y 3 from trial initiation.

References

Karsdal MA, Henriksen K, Leeming DJ, et al. Biochemical markers and the FDA critical path: how biomarkers may contribute to the understanding of pathophysiology and provide unique and necessary tools for drug development. Biomarkers. 2009;14(3):181-202. [CrossRef] [PubMed]
 
Lander ES, Linton LM, Birren B, et al; International Human Genome Sequencing Consortium. Initial sequencing and analysis of the human genome [published correction appears in Nature. 2001;411(6838):720]. Nature. 2001;409(6822):860-921. [CrossRef] [PubMed]
 
Cook D, Brown D, Alexander R, et al. Lessons learned from the fate of AstraZeneca’s drug pipeline: a five-dimensional framework. Nat Rev Drug Discov. 2014;13(6):419-431. [CrossRef] [PubMed]
 
Sacks LV, Shamsuddin HH, Yasinskaya YI, Bouri K, Lanthier ML, Sherman RE. Scientific and regulatory reasons for delay and denial of FDA approval of initial applications for new drugs, 2000-2012. JAMA. 2014;311(4):378-384. [CrossRef] [PubMed]
 
Scannell JW, Blanckley A, Boldon H, Warrington B. Diagnosing the decline in pharmaceutical R&D efficiency. Nat Rev Drug Discov. 2012;11(3):191-200. [CrossRef] [PubMed]
 
Calverley PM. New treatments for COPD: many miles still to go. Lancet Respir Med. 2014;2(1):6-7. [CrossRef] [PubMed]
 
 Paving the Way for Personalized Medicine: FDA’s Role in a New Era of Medical Product Development. Rockville, MD: US Food and Drug Administration; 2013.
 
Forde PM, Ettinger DS. Targeted therapy for non-small-cell lung cancer: past, present and future. Expert Rev Anticancer Ther. 2013;13(6):745-758. [CrossRef] [PubMed]
 
Accurso FJ, Rowe SM, Clancy JP, et al. Effect of VX-770 in persons with cystic fibrosis and the G551D-CFTR mutation. N Engl J Med. 2010;363(21):1991-2003. [CrossRef] [PubMed]
 
Burney P, Jithoo A, Kato B, et al; Burden of Obstructive Lung Disease (BOLD) Study. Chronic obstructive pulmonary disease mortality and prevalence: the associations with smoking and poverty–a BOLD analysis. Thorax. 2014;69(5):465-473. [CrossRef] [PubMed]
 
Smolonska J, Wijmenga C, Postma DS, Boezen HM. Meta-analyses on suspected chronic obstructive pulmonary disease genes: a summary of 20 years’ research. Am J Respir Crit Care Med. 2009;180(7):618-631. [CrossRef] [PubMed]
 
Vestbo J, Hurd SS, Agustí AG, et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. Am J Respir Crit Care Med. 2013;187(4):347-365. [CrossRef] [PubMed]
 
Segreti A, Stirpe E, Rogliani P, Cazzola M. Defining phenotypes in COPD: an aid to personalized healthcare. Mol Diagn Ther. 2014;18(4):381-388. [CrossRef] [PubMed]
 
Hurst JR, Vestbo J, Anzueto A, et al; Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) Investigators. Susceptibility to exacerbation in chronic obstructive pulmonary disease. N Engl J Med. 2010;363(12):1128-1138. [CrossRef] [PubMed]
 
Langsetmo L, Platt RW, Ernst P, Bourbeau J. Underreporting exacerbation of chronic obstructive pulmonary disease in a longitudinal cohort. Am J Respir Crit Care Med. 2008;177(4):396-401. [CrossRef] [PubMed]
 
Madani A, Zanen J, de Maertelaer V, Gevenois PA. Pulmonary emphysema: objective quantification at multi-detector row CT—comparison with macroscopic and microscopic morphometry. Radiology. 2006;238(3):1036-1043. [CrossRef] [PubMed]
 
Thomsen M, Ingebrigtsen TS, Marott JL, et al. Inflammatory biomarkers and exacerbations in chronic obstructive pulmonary disease. JAMA. 2013;309(22):2353-2361. [CrossRef] [PubMed]
 
Calverley PM, Sanchez-Toril F, McIvor A, Teichmann P, Bredenbroeker D, Fabbri LM. Effect of 1-year treatment with roflumilast in severe chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2007;176(2):154-161. [CrossRef] [PubMed]
 
Wedzicha JA, Rabe KF, Martinez FJ, et al. Efficacy of roflumilast in the COPD frequent exacerbator phenotype. Chest. 2013;143(5):1302-1311. [CrossRef] [PubMed]
 
Calverley PM, Rabe KF, Goehring UM, Kristiansen S, Fabbri LM, Martinez FJ; M2-124 and M2-125 Study Groups. Roflumilast in symptomatic chronic obstructive pulmonary disease: two randomised clinical trials. Lancet. 2009;374(9691):685-694. [CrossRef] [PubMed]
 
Vestbo J, Agusti A, Wouters EF, et al; Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints Study Investigators. Should we view chronic obstructive pulmonary disease differently after ECLIPSE? A clinical perspective from the study team. Am J Respir Crit Care Med. 2014;189(9):1022-1030. [CrossRef] [PubMed]
 
Decramer M, Celli B, Kesten S, Lystig T, Mehra S, Tashkin DP; UPLIFT Investigators. Effect of tiotropium on outcomes in patients with moderate chronic obstructive pulmonary disease (UPLIFT): a prespecified subgroup analysis of a randomised controlled trial. Lancet. 2009;374(9696):1171-1178. [CrossRef] [PubMed]
 
Calverley PM, Anderson JA, Celli B, et al; TORCH Investigators. Salmeterol and fluticasone propionate and survival in chronic obstructive pulmonary disease. N Engl J Med. 2007;356(8):775-789. [CrossRef] [PubMed]
 
Celli BR, Thomas NE, Anderson JA, et al. Effect of pharmacotherapy on rate of decline of lung function in chronic obstructive pulmonary disease: results from the TORCH study. Am J Respir Crit Care Med. 2008;178(4):332-338. [CrossRef] [PubMed]
 
Tashkin DP, Celli B, Senn S, et al; UPLIFT Study Investigators. A 4-year trial of tiotropium in chronic obstructive pulmonary disease. N Engl J Med. 2008;359(15):1543-1554. [CrossRef] [PubMed]
 
Vestbo J, Edwards LD, Scanlon PD, et al; ECLIPSE Investigators. Changes in forced expiratory volume in 1 second over time in COPD. N Engl J Med. 2011;365(13):1184-1192. [CrossRef] [PubMed]
 
Jenkins CR, Jones PW, Calverley PM, et al. Efficacy of salmeterol/fluticasone propionate by GOLD stage of chronic obstructive pulmonary disease: analysis from the randomised, placebo-controlled TORCH study. Respir Res. 2009;10:59. [CrossRef] [PubMed]
 
Fletcher C, Peto R, Tinker CM, et al. The Natural History of Chronic Bronchitis and Emphysema. New York, NY: Oxford University Press; 1976.
 
Svanes C, Sunyer J, Plana E, et al. Early life origins of chronic obstructive pulmonary disease. Thorax. 2010;65(1):14-20. [CrossRef] [PubMed]
 
Karsdal MA, Christiansen C, Ladel C, Henriksen K, Kraus VB, Bay-Jensen AC. Osteoarthritis—a case for personalized health care? Osteoarthritis Cartilage. 2014;22(1):7-16. [CrossRef] [PubMed]
 
Felson D, Niu J, Sack B, Aliabadi P, McCullough C, Nevitt MC. Progression of osteoarthritis as a state of inertia. Ann Rheum Dis. 2013;72(6):924-929. [CrossRef] [PubMed]
 
Vestbo J, Anderson W, Coxson HO, et al; ECLIPSE Investigators. Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points (ECLIPSE). Eur Respir J. 2008;31(4):869-873. [CrossRef] [PubMed]
 
Vestbo J, Rennard S. Chronic obstructive pulmonary disease biomarker(s) for disease activity needed—urgently. Am J Respir Crit Care Med. 2010;182(7):863-864. [CrossRef] [PubMed]
 
Stolz D, Kostikas K, Blasi F, et al. Adrenomedullin refines mortality prediction by the BODE index in COPD: the “BODE-A” index. Eur Respir J. 2014;43(2):397-408. [CrossRef] [PubMed]
 
Leeming DJ, Sand JM, Nielsen MJ, et al. Serological investigation of the collagen degradation profile of patients with chronic obstructive pulmonary disease or idiopathic pulmonary fibrosis. Biomark Insights. 2012;7:119-126. [CrossRef] [PubMed]
 
Kristensen JH, Karsdal MA, Genovese F, et al. The role of extracellular matrix quality in pulmonary fibrosis. Respiration. 2014;88(6):487-499. [CrossRef] [PubMed]
 
Wedzicha JA, Calverley PM, Seemungal TA, Hagan G, Ansari Z, Stockley RA; INSPIRE Investigators. The prevention of chronic obstructive pulmonary disease exacerbations by salmeterol/fluticasone propionate or tiotropium bromide. Am J Respir Crit Care Med. 2008;177(1):19-26. [CrossRef] [PubMed]
 
Mushtaq Y. The COPD pipeline. Nat Rev Drug Discov. 2014;13(4):253. [CrossRef] [PubMed]
 
Watz H, Barnacle H, Hartley BF, Chan R. Efficacy and safety of the p38 MAPK inhibitor losmapimod for patients with chronic obstructive pulmonary disease: a randomised, double-blind, placebo-controlled trial. Lancet Respir Med. 2014;2(1):63-72. [CrossRef] [PubMed]
 
Karsdal MA, Krarup H, Sand JM, et al. Review article: the efficacy of biomarkers in chronic fibroproliferative diseases - early diagnosis and prognosis, with liver fibrosis as an exemplar. Aliment Pharmacol Ther. 2014;40(3):233-249. [CrossRef] [PubMed]
 
Salazar LM, Herrera AM. Fibrotic response of tissue remodeling in COPD. Lung. 2011;189(2):101-109. [CrossRef] [PubMed]
 
Karsdal MA, Nielsen MJ, Sand JM, et al. Extracellular matrix remodeling: the common denominator in connective tissue diseases. Possibilities for evaluation and current understanding of the matrix as more than a passive architecture, but a key player in tissue failure. Assay Drug Dev Technol. 2013;11(2):70-92. [CrossRef] [PubMed]
 
Crosby LM, Waters CM. Epithelial repair mechanisms in the lung. Am J Physiol Lung Cell Mol Physiol. 2010;298(6):L715-L731. [CrossRef] [PubMed]
 
Kranenburg AR, Willems-Widyastuti A, Moori WJ, et al. Enhanced bronchial expression of extracellular matrix proteins in chronic obstructive pulmonary disease. Am J Clin Pathol. 2006;126(5):725-735. [CrossRef] [PubMed]
 
Finlay GA, O’Driscoll LR, Russell KJ, et al. Matrix metalloproteinase expression and production by alveolar macrophages in emphysema. Am J Respir Crit Care Med. 1997;156(1):240-247. [CrossRef] [PubMed]
 
Hallgren O, Nihlberg K, Dahlbäck M, et al. Altered fibroblast proteoglycan production in COPD. Respir Res. 2010;11:55. [CrossRef] [PubMed]
 
Sandhaus RA, Turino G. Neutrophil elastase-mediated lung disease. COPD. 2013;10(suppl 1):60-63. [CrossRef] [PubMed]
 
Churg A, Zhou S, Wright JL. Series “matrix metalloproteinases in lung health and disease”: matrix metalloproteinases in COPD. Eur Respir J. 2012;39(1):197-209. [CrossRef] [PubMed]
 
Karsdal MA, Bay-Jensen AC, Leeming DJ, Henriksen K, Christiansen C. Quantification of “end products” of tissue destruction in inflammation may reflect convergence of cytokine and signaling pathways—implications for modern clinical chemistry. Biomarkers. 2013;18(5):375-378. [CrossRef] [PubMed]
 
Skjøt-Arkil H, Clausen RE, Nguyen QH, et al. Measurement of MMP-9 and -12 degraded elastin (ELM) provides unique information on lung tissue degradation. BMC Pulm Med. 2012;12(1):34. [CrossRef] [PubMed]
 
Leeming Dj, He Y, Veidal S, et al. A novel marker for assessment of liver matrix remodeling: an enzyme-linked immunosorbent assay (ELISA) detecting a MMP generated type I collagen neo-epitope (C1M). Biomarkers. 2011;16(7):616-628. [CrossRef] [PubMed]
 
Segovia-Silvestre T, Reichenbach V, Fernández-Varo G, et al. Circulating CO3-610, a degradation product of collagen III, closely reflects liver collagen and portal pressure in rats with fibrosis. Fibrogenesis Tissue Repair. 2011;4:19. [CrossRef] [PubMed]
 
Veidal SS, Larsen DV, Chen X, et al. MMP mediated type V collagen degradation (C5M) is elevated in ankylosing spondylitis. Clin Biochem. 2012;45(7-8):541-546. [CrossRef] [PubMed]
 
Veidal SS, Karsdal MA, Nawrocki A, et al. Assessment of proteolytic degradation of the basement membrane: a fragment of type IV collagen as a biochemical marker for liver fibrosis. Fibrogenesis Tissue Repair. 2011;4(1):22. [CrossRef] [PubMed]
 
Bay-Jensen AC, Liu Q, Byrjalsen I, et al. Enzyme-linked immunosorbent assay (ELISAs) for metalloproteinase derived type II collagen neoepitope, CIIM—increased serum CIIM in subjects with severe radiographic osteoarthritis. Clin Biochem. 2011;44(5-6):423-429. [CrossRef] [PubMed]
 
Bay-Jensen AC, Platt A, Byrjalsen I, Vergnoud P, Christiansen C, Karsdal MA. Effect of tocilizumab combined with methotrexate on circulating biomarkers of synovium, cartilage, and bone in the LITHE study. Semin Arthritis Rheum. 2014;43(4):470-478. [CrossRef] [PubMed]
 
Veidal SS, Karsdal MA, Vassiliadis E, et al. MMP mediated degradation of type VI collagen is highly associated with liver fibrosis—identification and validation of a novel biochemical marker assay. PLoS One. 2011;6(9):e24753. [CrossRef] [PubMed]
 
Genovese F, Barascuk N, Larsen L, et al. Biglycan fragmentation in pathologies associated with extracellular matrix remodeling by matrix metalloproteinases. Fibrogenesis Tissue Repair. 2013;6(1):9. [CrossRef] [PubMed]
 
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