Approaches to Integrating Biomarkers Into Clinical Trials and Care Pathways as Targets for the Treatment of Inflammatory Bowel Diseases

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Approaches to Integrating Biomarkers Into Clinical Trials and Care Pathways as Targets for the Treatment of Inflammatory Bowel Diseases Parambir S. Dulai,1 Laurent Peyrin-Biroulet,2 Silvio Danese,3 Bruce E. Sands,4 Axel Dignass,5 Dan Turner,6 Gerassimos Mantzaris,7 Juergen Schölmerich,8 Jean-Yves Mary,9 Walter Reinisch,10 and William J. Sandborn1 1 Division of Gastroenterology, University of California San Diego, La Jolla, California; 2Department of Gastroenterology, Nancy University Hospital, Lorraine University, Nancy, France; 3Department of Biomedical Sciences, Humanitas University, Humanitas Clinical and Research Centre, Milan, Italy; 4Dr Henry D. Janowitz Division of Gastroenterology, Icahn School of Medicine at Mount Sinai, New York, New York; 5Department of Medicine I, Agaplesion Markus Hospital and Crohn Colitis Clinical Research Center Rhein-Main, Frankfurt/Main, Germany; 6Institute of Paediatric Gastroenterology, Shaare Zedek Medical Center, The Hebrew University of Jerusalem, Jerusalem, Israel; 7Department of Gastroenterology, Evaggelismos-Ophthalmiatreion Athinon-Polycliniki, Athens, Greece; 8Goethe University, Frankfurt, Germany; 9 INSERM UMR, Paris Diderot University, Saint Louis Hospital, Paris, France; and 10Universitätsklinik für Innere Medizin III, Vienna, Austria

BACKGROUND & AIMS: There is no consensus on the best way to integrate biomarkers into inflammatory bowel disease (IBD) research and clinical practice. The International Organization for the Study of Inflammatory Bowel Disease aimed to outline biomarker definitions, categories, and operating properties required for their use in registration trials and clinical practice. Using fecal calprotectin as an example, we provide a framework for biomarker development and validation in patients with IBD. METHODS: We reviewed international society guidelines, regulatory agency guidance documents, and standardized reporting guidelines for biomarkers, in combination with publications on fecal calprotectin levels in patients with IBD. We assessed the validity of fecal calprotectin to serve as a surrogate biomarker of IBD activity and outlined a framework for further validation and development of biomarkers. RESULTS: No endpoints have been fully validated as surrogates of risk of disease complications; mucosal healing is the most valid endpoint used to determine risk of disease complications. Fecal level of calprotectin has not been validated as a biomarker for IBD activity because of lack of technical and clinical reliability, assessment of performance when used as a replacement for endoscopy, and assessment of responsiveness to changes in disease states. The level of fecal calprotectin can be used only as a prognostic factor for disease recurrence in patients in remission after medical or surgical treatment. CONCLUSIONS: We reviewed guidelines, regulatory documents, and publications to identify properties required for the development of biomarkers of IBD activity and areas in need of clarification from regulatory agencies and societies. We propose a path forward for research of biomarkers for IBD.

Keywords: Crohn’s Disease; Ulcerative Colitis; Outcome; Response to Treatment.

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ignificant progress has been made in drug development for Crohn’s disease (CD) and ulcerative colitis (UC). There has also been an increasing emphasis placed on appropriate end point selection and disease activity monitoring, due largely to an evolving appreciation of how misinterpretation of inflammatory vs clinical disease activity can affect clinical trial success and clinical decision making. Endoscopy represents the criterion standard of objective disease activity assessment, requiring central blinded reading to ensure reproducible, unbiased assessment. In routine practice, endoscopy can be associated with considerable cost, risk, and burden to patients and health care systems, and from a patient perspective, endoscopybased monitoring is ranked least acceptable.1 Biomarkers are objectively measured and evaluated assessments of normal or pathogenic biologic processes and/ or pharmacologic responses to therapeutic interventions.2 The use of biomarkers in inflammatory bowel disease (IBD) has largely been limited to noninvasive adjunctive assessment of disease activity and is not approved by regulatory agencies to be predictive nor to be a surrogate of a further clinical endpoint.3 There is no consensus on and only limited knowledge about how to optimally integrate biomarkers into IBD research and clinical practice. A framework for biomarker validation and integration into

Abbreviations used in this paper: ACG, American College of Gastroenterology; AGA, American Gastroenterological Association; CD, Crohn’s disease; CRP, C-reactive protein; ECCO, European Crohn’s and Colitis Organization; EMA, European Medicines Agency; FC, fecal calprotectin; FDA, US Food and Drug Administration; IBD, inflammatory bowel diseases; MH, mucosal healing; UC, ulcerative colitis. © 2019 by the AGA Institute 0016-5085/$36.00 https://doi.org/10.1053/j.gastro.2019.06.018

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BACKGROUND AND CONTEXT

full-text studies relevant to FC in IBD. The Standards for Reporting Diagnostic Accuracy were also reviewed to capture fundamental pillars in biomarker reporting for FC in IBD.5

There is no consensus on the best way to integrate biomarkers into inflammatory bowel disease (IBD) research and clinical practice.

Biomarker Categories

WHAT YOU NEED TO KNOW

NEW FINDINGS

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No endpoints have been validated for studies of IBD. Fecal level of calprotectin has not been validated as a biomarker for IBD activity. Level of fecal calprotectin can be used only as a prognostic factor for relapse following treatment. LIMITATIONS This was a review of guidelines, regulatory agency guidance documents, and publications, in combination with expert opinion. IMPACT The authors propose a path forward for research of biomarkers for IBD.

practice would potentially have utility in both early- and late-stage drug development and in clinical practice. In the current review we outline definitions and characteristics of biomarkers and operating properties of importance for both registration trials and for clinical practice, and we propose a path forward for surrogate biomarker development in IBD, using fecal calprotectin (FC) as an example.

Methods The Endpoints Cluster Group of the International Organization for the Study of Inflammatory Bowel Diseases (IOIBD) met on March 17, 2018, in Rio de Janeiro, Brazil, and decided to write an article on biomarkers and biomarker qualification for regulatory approval, using FC as the example. The cluster group members were polled regarding interest in participating, and a subgroup of the members volunteered and became the authors of the article. Parambir S. Dulai was invited to participate by the group lead, William J. Sandborn, with the consent of the other authors. The final article was reviewed by the entire membership of the Endpoints Cluster Group and by the Chairman of the IOIBD, Geert D’Haens. A review of the US Food & Drug Administration (FDA) and the European Medicines Agency (EMA) Web sites was conducted for guidance documents on clinical trials in IBD and/or biomarkers. This included the BEST (Biomarkers, EndpointS, and other Tools) Resource prepared by the FDA and National Institutes of Health.4 A review of the American Gastroenterology Association (AGA) (https://www.gastro.org/guidelines/ ibd-and-bowel-disorders), American College of Gastroenterology (ACG) (http://gi.org/clinical-guidelines/clinical-guide lines-sortable-list/) and European Crohn’s and Colitis Organization (ECCO) (https://www.ecco-ibd.eu/publications/eccoguidelines-science/published-ecco-guidelines.html) Web sites was conducted for IBD-specific guidelines and technical reviews to identify statements relevant to biomarkers and/or the integration of biomarkers into clinical trials or care pathways. A search of PubMed was conducted for studies related to calprotectin, and 4060 titles and/or abstracts were screened for

A summary of key biomarker-specific terms and their importance to IBD is provided in Table 1. Important definitions and distinctions are summarized here:
Diagnostic biomarker: Used to detect or confirm the presence of a disease or condition and assessed through cross-sectional studies of biomarker measurements and disease activity measurements at the same time point.
Monitoring biomarker: Measured serially over time to evaluate changes in biomarker and disease state and assessed through longitudinal studies in which variation of the biomarker and change in clinical disease activity or in disease states are measured in the same time frame.
Prognostic or predictive biomarker: Assessed through longitudinal studies of the biomarker at a given time point and of clinical disease activity or disease complication occurrence during subsequent follow-up or at a later time point. A prognostic biomarker reflects an individual patient’s intrinsic probability of experiencing a specific event (ie, disease recurrence, progression, complication, or surgery), often derived from observational data. An example of this is a tool that stratifies an individual patient’s probability of experiencing a disease-related complication or recurrence or of requiring surgery (irrespective of treatment exposure).6,7 A predictive biomarker reflects the ability to identify individuals with a positive biomarker who are more likely than similar individuals with a negative biomarker to experience a favorable effect from exposure to a specific intervention, best derived from clinical trial data. An example of this is a tool that stratifies an individual patient’s probability of responding to therapy (specific to treatment exposure).8 The integration of prognostic and predictive biomarkers is possible by showing that a specific therapy may be effective in both patients with a positive predictive biomarker and those with a negative predictive biomarker; however, the effect size is larger among a subgroup of patients based on the status of their prognoses related to a diseaserelated complication.
Composite biomarker: A combination of 2 or more biomarkers, which are combined by using a stated algorithm or approach to obtain a single interpretive readout. An example of this can be taken from nonalcoholic fatty liver disease, for which magnetic resonance imaging–based noninvasive assessments (ie, biomarkers) of fat quantity (magnetic resonance imag- Q7 ing–proton-density fat fraction) and hepatic fibrosis (magnetic resonance elastography) are combined into a single interpretative readout to inform the full spectrum of disease progression and regression and the prognostication of disease outcomes.2

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Table 1.Key Biomarker Terminology and Description

Diagnostic

FDA–NIH definition

FDA–NIH explanation

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Detect or confirm presence of a Determination of whether a patient has a disease or condition of particular medical condition for which interest OR identify treatment may be indicated OR whether individuals with a subtype of an individual should be enrolled in a the disease clinical trial studying a particular disease or subtype of the disease. Monitoring Measured serially for assessing Serial nature of the measurements focuses attention on change in the biomarker’s status of a disease or value as an indicator of an individual’s medical condition or for current or future condition, beneficial or evidence of exposure to (or adverse effect of a drug or other effect of) a medical product intervention, or effect of an exposure or an environmental agent over time. Can include other biomarker types when measured serially. Pharmacodynamic Show that a biological response Level changes in response to an exposure or response has occurred in an individual and provides early evidence that a (application of who has been exposed to a treatment might have an effect on a monitoring) medical product or an clinical endpoint of interest or can be environmental agent used to assess a pharmacologic endpoint related to safety concerns.

Predictive

Prognostic

Importance in clinical trials (enrichment strategies)

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Term

Operating properties to be assessed and examples

Decrease heterogeneity: Accurate classification Accuracy, Precision, Reliability of disease, activity state, severity, and/or Identify IBD and subtypes and quantify distribution of involvement extent and severity of involvement Increase study power and the ability to EF in patients with HF to identify subsets demonstrate a treatment effect of disease state Responsiveness Decrease heterogeneity during screening: Detect worsening or improvement in disease Confirm persistent stable activity before treatment and tolerability/adequate before enrollment exposure/response during treatment Decrease heterogeneity during active treatment: LFTs to monitor toxicity Confirm drug concentration/exposure and rate of response, progression, or toxicity

Responsiveness, Feasibility Ease of monitoring regression or progression of inflammation after an intervention without the need for invasive testing HCV-RNA or HIV-RNA to measure response and guide further treatment

Accuracy, Reliability Identify patients likely to respond to specific interventions TPMT genotype or activity for treatment with thiopurines to predict toxicity

Accuracy, Reliability Balanced randomization based on clinical prediction models for disease progression and/or complication Gleason score for progression of prostate cancer under therapy

Adapted from FDA-NIH BEST Resource.4 EF, ejection fraction; HCV, hepatitis C virus; HF, heart failure; LFT, XXXX; NIH, National Institutes of Health; TPMT, thiopurine methyltransferase.

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Enrichment through randomized withdrawal: Empiric strategy whereby patients with an apparent response to treatment (during open-label or treatment arm) are randomly reassigned to receive drug or placebo Establish long-term effectiveness when longterm use of placebo not acceptable or high dropout and avoid long-term exposure to ineffective drug Predictive strategy: Selecting patients more Used either to select patients for Identify at baseline individuals participation or to stratify patients into likely to respond to an intervention who are more likely than (positively or negatively) compared with biomarker-positive and biomarkersimilar individuals without negative groups, with the other patients with the condition the biomarker to experience primary endpoint being the effect in the Increase absolute and relative effect size, a favorable or unfavorable biomarker-positive group. reduction in size of study population needed, effect from exposure to a and enhanced benefit to risk relationship medical product or an (ideal for early-phase proof-of-concept trials) environmental agent Prognostic strategy: Selecting patients more Identify baseline likelihood of a Indicates an increased (or decreased) likely to have clinical events of interest or to clinical event, disease likelihood of a future clinical event, progress rapidly with substantial worsening recurrence, or progression in disease recurrence, or progression in an identified population. Measured at of the condition being treated patients who have the Increase absolute effect size between groups defined baseline and therefore may disease or medical condition include background or prior treatments (ideal for prevention trials) with some impact of interest on the size of study population needed

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Endpoint Definitions for Biomarker Studies It is important to consider the endpoint against which the biomarker is being assessed and to validate whether that endpoint may serve as a surrogate for disease effects, net benefits of interventions, and/or future clinical events.

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Reasonably likely surrogate endpoint: An endpoint supported by strong mechanistic and/or epidemiologic rationale such that an effect on the surrogate endpoint is expected to be correlated with an endpoint intended to assess clinical benefit in clinical trials but without sufficient clinical data to show that it is a validated surrogate endpoint. Symptom-based indices have served as a prime example of a noninvasive assessment previously believed to be a reasonably likely surrogate endpoint in IBD trials, despite the lack of evidence supporting an association between resolution of symptoms with reduction in diseaserelated complications.
Validated surrogate endpoint: An endpoint supported by a clear mechanistic rationale and clinical data providing strong evidence that an effect on the surrogate endpoint predicts a specific clinical benefit. Achieving mucosal healing (MH) is an early example of a possibly validated surrogate endpoint, given its clear association with reductions in several disease-related complications,9 however, it is not enough for an early surrogate endpoint (ie, MH) to correlate with a later clinical endpoint (diseaserelated complications) for it to be considered a validated surrogate endpoint. The effect of the intervention on the surrogate endpoint must reliably predict or fully capture the net effect of the intervention on the clinical outcome.4,10,11 Indeed, this is not straightforward to prove because many confounding factors may be at the origin of a correlation between the observation of a possibly surrogate endpoint and an observed favorable further clinical outcome. The randomized clinical trial is an attractive method in this situation, as are promising new methods that deal with causal effects.12 A randomized trial by Landi et al13 assessed the validity of endoscopic remission serving as a surrogate endpoint of future clinical relapse among patients with colonic CD being treated with steroids for acute flares. The study enrolled 147 patients with CD being treated with oral prednisolone for an acute flare, of whom 136 achieved clinical remission. Endoscopic activity was observed in 96 of these 136, and these 96 patients were subsequently randomly assigned to receive immediate steroid taper (n ¼ 46) or prolonged prednisolone for 5 weeks with subsequent taper (n ¼ 50); the remaining 40 patients who had achieved both clinical remission and endoscopic remission had immediate steroid tapering. Although the prolonged steroid treatment before tapering resulted in an improved endoscopic remission rate, there were no significant differences across groups in terms of clinical relapse after steroid withdrawal. That study was performed before the development and validation of endoscopic disease activity indices, and endoscopic remission was empirically defined as no lesion at all, or only

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scarred lesions, or minor lesions with at least a 2-grade decrease on a 6-grade scale and no deep ulceration. However, it does provide insight and framework into how a trial may be used to validate MH as a surrogate endpoint and highlights the facts that fully capturing the relationship is not easy to prove and that most endpoints presented as surrogate endpoints of a more distant clinical endpoint do not fulfill this requirement. Therefore, although MH is not a fully validated surrogate endpoint, it is considered our most valid surrogate endpoint of many further disease complications, and this is now being considered a requirement as an endpoint in IBD trials. Ideal biomarkers in IBD are those that measure (diagnostic), monitor (pharmacodynamics/responsive), predict, or prognosticate previously recognized and validated surrogate endpoints for disease-related complications. For this reason, any future consideration for biomarker integration into clinical trials and clinical practice for IBD will need to focus on a comparison of biomarkers to disease remission (mucosal and transmural healing) and the ability to measure, monitor, predict, or prognosticate the achievement of remission across diseases (CD and UC) and subtypes (disease location and/or disease-related complication–specific groups).9

Assessment of Biomarker Operating Properties A summary of technical and clinical operating properties (including their components) for biomarkers and their implications for clinical trials can be found in Figure 1.
Reliability: The consistency in repeated measures when the Q8 measured concept has remained unchanged or its ability to give the same answer every time. It is usually expressed as the intraclass correlation coefficient estimate.
Accuracy: The extent to which a biomarker measures the outcome it was intended to measure. For measuring disease remission, when the biomarker is used as a continuous marker, accuracy may be expressed as a receiver operating characteristic area under the curve or a concordance index (C-index), whereas when assessing operating properties related to a given threshold of a biomarker, accuracy may be expressed as sensitivity (ability to rule out active inflammation), specificity (ability to rule in active inflammation), predictive values (negative or positive), and/or likelihood ratios (negative or positive). Negative and positive predictive values provide the distinct advantage of being able to take into consideration both diagnostic accuracy (sensitivity/ specificity) and diagnosis prevalence (proportion of patients with MH) in the studied population to provide estimates of the test performance. However, these estimates depend on the observed prevalence in the sample, which therefore limits generalizability. Negative and positive likelihood ratios outline the likelihood that the patient has the outcome of interest and do not depend on outcome prevalence. A positive likelihood ratio expresses the probability of being classified as positive by

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Figure 1. Technical and clinical operating properties of biomarkers and implications for clinical trials. Reliability can relate to the technical side of performing the assay and the clinical side of variation between measured patients. Technical aspects of reliability focus on intra-assessments and interassessments of an operator (the same operator twice for the same sample or 2 individual operators for the same sample), laboratory or lot (sources of samples), day (timing of collection during day), and extraction or recovery (separate extractions of the same sample or different samples of varying concentrations). Clinical aspects of reliability focus on intra-assessments and interassessments of a patient (the same patient assessed twice without change in reference activity measure or 2 patients with similar reference activity measures), treatment (different or similar treatments), and disease subtype (presence or absence of complications or alterations, eg, strictures or fistulae).

the biomarker among patients having the outcome to the same probability among patients not having the outcome. In addition, the ratio of the negative and positive likelihood ratios provides the odds ratio estimate of the association between the biomarker result and the outcome.
Responsiveness: The ability of a biomarker to measure meaningful changes in disease states, which can be presented in 1 of 3 ways: biomarker correlations to changes in reference measures of disease status, consistency in biomarker accuracy measures across disease states, and distributional methods (ie, Cohen or Guyatt statistics) that evaluate changes in the biomarker and its associated variability (ie, standard deviation).14 Optimizing reliability, accuracy, and responsiveness across treatment interventions and patient subgroups, can minimize the sample size required for a clinical trial.10,11,15,16 Optimization of these operating properties can be performed at each stage of assessment through colocalization or composite biomarker strategies, such as the combination of FC with C-reactive protein (CRP) level to optimize the detection of mucosal inflammation17 or the use

of 2 or more diagnostic assessment modalities to obtain 100% accuracy for determining fistula anatomy in patients Q9 with CD with perianal disease.18 The accuracy and responsiveness are strongly influenced by the reference measurement (ie, criterion standard), and when an operating characteristic is estimated in a sample through a rule derived from the same sample, the quality of this characteristic is overestimated, and validation is necessary on a new independent sample. Thus, for disease remission in IBD (mucosal and/or transmural healing), factors such as blinding or adjudication of endoscopic or radiographic scoring, disease activity indices, segment-specific scoring, combination of endoscopy with histologic or radiographic assessment of transmural healing, and external validation in additional cohorts are important.

Importance of Validated Biomarkers for Drug Development in Inflammatory Bowel Disease The 21st Century Cures Act highlighted the importance of biomarker qualification as drug development tools to accelerate development of new safe and effective drugs and

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biologics. The FDA has accordingly now placed a greater focus on the generation of data and evidence needed to support biomarker development for these purposes. The implications of validated biomarkers on clinical trial design are highlighted in Figure 1. With regard to drug development programs specifically, validated biomarkers have 3 key potential roles: assessment of desired biochemical effect (exposure-response), providing early feedback for preclinical decision making (go/no go), and targeting recruitment to study participants most likely to respond or progress within a reasonable and manageable clinical study time frame (prognostic).19 A biomarker validated for a surrogate endpoint such as MH could be of value as a response criterion within early dose-finding studies to overcome the lack of granularity in responsiveness of currently available indices. Subsequent use of the validated biomarker for a remission criterion would allow for efficient and costeffective assessments of treatment effectiveness vs placebo or standard of care to allow for early go/no-go decision making. Finally, if the biomarker is validated against an endpoint that is a true surrogate for a future event (clinical relapse or surgery), it could be used to stratify patient recruitment into specific trials focusing on prevention strategies within an umbrella or basket trial design platform, or it could be used as a trial endpoint to obtain a more rapid assessment and comparison between treatment arms without requiring the longer follow-up periods traditionally needed for the occurrence of rare events (ie, surgery).20

(FC or CRP) vs confirmation with colonoscopy in symptomatic patients with CD, but this may depend on whether there is historically good correlation between the biomarker selected and colonoscopy in the specific patient. In symptomatic patients with CD without inflammatory markers, the AGA guidance specifically comments on performing cross- Q10 sectional imaging; however, in symptomatic patients with CD with inflammatory markers, the guidance does not make any recommendations on cross-sectional imaging. ECCO guidelines for CD state that CRP and FC can be used to guide therapy and short-term follow-up and to predict clinical relapse. However, no recommendation is made on how to position these biomarkers within treatment care pathways or what their role should be in replacing or augmenting endoscopic evaluations.25 It should be noted that these recommendations were made before the completion of the Q11 CALM trial and will likely need to be updated.17 The AGA UC care pathway recommends testing for CRP but makes no specific recommendations for FC and still recommends the use of lower endoscopy in all patients to determine inflammatory status. The ECCO guidelines for UC note the value of CRP and FC for prognostication of disease risk (colectomy in acute severe UC) and relapse, and they acknowledge the diagnostic value of FC for assessing mucosal inflammatory status and severity. However, no specific recommendation is made on its use to guide therapy and short-term follow-up in UC.26,27

Current State of Biomarkers in Inflammatory Bowel Disease Clinical Trials and Clinical Practice

Fecal Calprotectin in Inflammatory Bowel Disease

The FDA and the EMA both encourage the collection of biomarkers to facilitate the monitoring of FDA-regulated products and their appropriate use in clinical practice; however, both agencies state that these biomarkers may not be used to support labeling claims. The EMA outlines that this rationale is due to the inability of currently available biomarkers to provide standalone evidence of inflammation, and the FDA highlights the fact that no established biomarker can be relied on to establish an exposure-efficacy relationship. FDA guidance has been provided for the development of FC immunologic tests21; however, there are no specific guidelines or consensus statements pertaining to the use of biomarkers in clinical trials. AGA, ACG, and ECCO guidance documents all note a growing recognition of the diagnostic performance of FC for assessing the absence of endoscopic recurrence postoperatively in CD and the need for future studies comparing endoscopy to biomarker-based decision making.22–24 The AGA CD care pathway and ACG CD clinical guideline acknowledge the adjunctive value of FC for monitoring disease activity and response to therapy; however, they specifically note that biomarkers should not be used exclusively to serve as endpoints for treatment and that endoscopy is still required to confirm the absence of mucosal inflammation. The AGA states that consideration could be given to making treatment decisions based on inflammatory markers

The FDA defines FC as an immunologic test system intended for in vitro diagnostic use as an aid in the diagnosis of IBD.21 There is currently no mention of FC as a diagnostic biomarker to quantify the extent or severity of inflammation or for its use as a biomarker of responsiveness, prognostic and/or predictive performance.

Reliability FC has a significant variability across platforms and collection techniques (point of care vs send out, commercial extraction vs manual weighting), leading to low reliability28–33 (Supplementary Table 1). This variability translates to meaningful differences in diagnostic accuracy in some studies but not all.29,30,34,35 Although the literature and the multiple company device inserts suggest that no significant degradation in FC occurs until after 3 days at room temperature,36 a 12% decline in FC levels has been observed within 24 hours after stool collection irrespective of storage temperature.29 FC has been observed to have reasonable intra-stool correlations (intraclass correlation, 0.79; 95% confidence interval, 0.48–0.90)36; however, the inter-stool correlations are quite variable and significantly influenced by factors such as timing of collection within the day, physical attributes and characteristics of stool provided, and time between bowel movements (ie, stool frequency).36–40 The individual coefficient of variation for samples collected

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throughout a single day has been reported to be as high as 52%,36,37 with nearly one quarter of this variability being clinically significant and affecting the interpretation of the test.39,41 It has been suggested that the first stool sample of the day in combination with an FC cutoff of 250 mg/g will result in the most consistent measurement of disease activity and most reliable differentiation between MH and mucosal inflammation.39,42

Accuracy

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Several studies have derived overall pooled sensitivity and specificity estimates for FC from the meta-analysis of several studies using different cutoffs for assessing mucosal disease activity in both UC and CD43,44; however, this has several inherent limitations worth noting and of importance when understanding how to integrate biomarkers as treatment targets. The dichotomization of a continuous variable will result in a loss of overall diagnostic performance, but this dichotomization is of clinical utility when understanding how results should be used to guide treatment decisions. The choice for what value should be set for dichotomization depends on whether the objective is to optimize sensitivity (rule out disease) or specificity (rule in disease). Attempts can be made to identify a threshold that optimizes selection for both (ie, Youden index); however, this will invariably sacrifice performance in both domains for the sake of balance. Therefore, when interpreting accuracy of FC, we must consider cutoffs separately and not as overall pooled estimates and then consider the context within which they are being used. This is best shown in a recent meta-analysis in which the overall pooled sensitivity and specificity for FC (cutoffs, 48–400 mg/g) in IBD were reported to be 0.85 and 0.75, respectively. However, when looking at separate cutoffs individually, the overall sensitivity and specificity were reported to be 0.91 and 0.61, respectively, when using a cutoff of 50 mg/g and 0.88 and 0.67 when using a cutoff of 100 mg/g.45 A separate meta-analysis similarly showed that the overall sensitivity and specificity for FC in IBD were 0.92 and 0.60, respectively using a cutoff of 50 mg/g, 0.84 and 0.66 when using a cutoff of 100 mg/g, and 0.80 and 0.82 when using a cutoff of 250 mg/g.46 These studies have all observed that the diagnostic performance of FC is better in UC than CD; however, they have often combined different CD phenotypes together for analyses. For postoperative endoscopic recurrence detection in CD, the overall sensitivity and specificity of FC were 0.90 and 0.36, respectively, when using a cutoff of 50 mg/g, 0.81 and 0.57 when using a cutoff of 100 mg/g, 0.70 and 0.69 when using a cutoff of 150 mg/g, and 0.55 and 0.71 when using a cutoff of 200 mg/g.47 For small bowel CD confirmed by capsule endoscopy, the overall sensitivity and specificity of FC was 0.83 and 0.53, respectively, when using a cutoff of 50 mg/g and 0.42 and 0.94 using a cutoff of 200 mg/g.48

Composite Biomarker Strategy to Optimize Accuracy of Fecal Calprotectin Few studies have examined the use of composite biomarker strategies to optimize the diagnostic

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performance of FC in patients with established IBD. These studies have largely focused on improvements in overall accuracy (area under the curve) when combining stool or serum biomarkers with FC.49–53 However, this is of limited value for understanding the clinical utility of adding additional biomarkers to FC for disease activity assessment because it does not allow for an assessment of incremental diagnostic yield with prespecified cutoffs for each successive biomarker added. Post hoc analyses of CALM have recently attempted to address this gap when considering the addition of CRP to FC. When dealing with patients for whom both CRP and FC were evaluated at week 48, 66% (n ¼ 58/ 88) of patients with a CRP level < 5 mg/L and 75% (n ¼ 71/95) of patients with an FC level < 250 mg/g were observed to have MH (Crohn’s Disease Endoscopic Index of Severity < 4 and no deep ulcer). When combining the 2 biomarkers, 79% (n ¼ 55/70) of patients who had a CRP level < 5 mg/L and FC level < 250 mg/g were observed to have MH. Among patients who had a CRP level < 5 mg/L but an FC level  250 mg/L, only 17% (n ¼ 3/18) were observed to have MH, whereas 64% (n ¼ 16/25) of patients with a CRP level  5 mg/L but an FC level < 250 mg/L were observed to have MH. This shows that a composite biomarker strategy requiring both CRP and FC values to be below or above prespecified cutoffs improves the overall sensitivity and specificity for MH,54 and it is FC that adds the greatest incremental yield in diagnostic performance, leading to the majority of treatment escalation within this composite strategy.55

Responsiveness There is an overall paucity of literature surrounding the responsiveness of FC in IBD, particularly in CD. Post hoc analyses of UC clinical trials have observed that changes in FC correlate with meaningful changes in health status at a group level (ie, group average). However, at an individual level, the diagnostic accuracy was only fair to good for classifying clinical and endoscopic outcomes in clinical trials.56–59 Blinding of investigators to the reference standard significantly affected the heterogeneity of accuracy for biomarkers and, thus, should also be considered when evaluating the diagnostic accuracy and/or responsiveness of FC.43

Prognostic and/or Predictive Capacity FC measurements have been proposed for prognosticating and monitoring the risk of relapse,60,61 predicting disease course and progression,62,63 predicting risk of treatment failure or need for therapy escalation,64,65 and predicting future achievement of disease remission.66,67 A recent systematic review pooled studies following patients with IBD in clinical remission who had at least 2 serial FC measurements and quantified the ability of serial FC to prognosticate the risk for future disease relapse.68 Although the cutoffs varied across studies, the review observed that asymptomatic patients with IBD who had repeatedly elevated FC measurements were 53%–83% more likely to have clinical disease relapse in the 2–3 months after testing.

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Table 2.Components of Biomarker Qualification for Use in Clinical Trials and Clinical Practice

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Areas in need of clarification

Evidence concerns for FC

Technical reliability

Minimally acceptable variability between operators, laboratories, lots, samples, extraction techniques, and storage conditions, with specific focus on the clinical impact and/or impact on trial result outcomes.

Clinical reliability

Minimally acceptable variability between samples for an individual, different individuals, collection techniques, and disease-specific subpopulations with characteristics known to (or considered to be biologically plausible reasons to) affect reliability of measurements (ie, short gut in CD and bowel transit time on stool frequency). Thresholds of acceptability in sensitivity/specificity for patients, providers, payors, and other key stakeholders to allow for integration of biomarkers. Clinical situation–specific assessments of accuracy to guide study design for the assessment of operating properties (ie, cutoff for identifying MH to serve as treatment target and cutoff for identifying inflammation to guide therapy adjustments). Standardization of reference criterion standard for disease activity measurement. Degree of correlation needed to reference changes in health status, standardization of reference criterion standard for changes in health status.

Assessed, but significant variability across platforms and collection techniques observed. Minimally acceptable variability with focus on clinical impact not known. Requires further investigation regarding the impact of variability on clinical decision making to identify acceptable variability. Found to have significant variability throughout the day, with substantial impact on clinical interpretation. Requires optimization through an integrated approach combining clinical characteristics affecting reliability with variation in sampling techniques.

Diagnostic accuracy

Responsiveness

Prognostic

Ranking of outcomes by importance for prognostication, and strength of association needed. Interchangeability of prognostic performance for a possible surrogate endpoint (ie, MH).

Predictive

Ranking outcomes by importance for prediction, and strength of association needed. Interchangeability of prognostic performance for reasonably likely surrogate endpoint (ie, predicting clinical response interchangeable with predicting ultimate achievement of MH).

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Operating property

Cut offs identified to maximize sensitivity and specificity; early validation when using these cutoffs as interim monitoring tools. No formal assessment of FC as a replacement for endoscopic assessments, and assessments required using more stringent references (blinded evaluations of endoscopy/histology). Consistency in accuracy across drug classes required.

Early assessment in post hoc analyses of UC trials, limited assessment of responsiveness in CD. Unclear if effect size is comparable to reference criterion standard and how variability in measurements affects responsiveness. Prognostic performance for relapse established, but no assessments of prognostic performance for achieving MH, transmural healing, and/or risk of hospitalization or surgery (agnostic of treatment/intervention). Early assessment for treatment-/intervention-specific predictive performance, and integration with other available biomarkers; further validation required with specific cutoffs.

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Conversely, patients with repeated normal FC values were 67%–94% more likely to remain in clinical remission in the 2–3 months after testing. Similarly, the POCER trial observed that in postoperative patients with CD who were in endoscopic remission at 6 months, an FC value of >50 mg/g had 0.68 specificity for the development of future endoscopic recurrence at 18 months.59 These data help support the potential prognostic value of FC when used serially as a monitoring biomarker, and the integration of FC with colonoscopy for disease monitoring appears to be cost effective in the management of IBD.69 Across all studies taken together, an FC cutoff of 50 mg/g or 100 mg/g optimized sensitivity (ability to rule out active inflammation), and a cutoff of 250 mg/g optimized specificity (ability to rule in active inflammation). Consideration may therefore be given to 1 cutoff serving as a treatment endpoint (ie, confirmation that disease remission has been achieved) and another cutoff serving as treatment monitoring (ie, confirmation that inflammation is still present and treatment adjustments should be made).17,70,71 However, FC cutoffs will likely evolve in parallel with evolving therapeutic goals (ie, histologic healing or modified definitions for endoscopic and radiographic healing), and further assessments will be required for the performance of FC in assessing transmural healing in CD72 and across different drug classes with more focused and immunespecific mechanisms of action. Furthermore, none of these studies assessed the replacement of endoscopy with FCbased monitoring algorithms as a treatment target, and all of these approaches have yet to be fully studied in UC.

Needs Assessment for Biomarker Qualification in Inflammatory Bowel Disease and Future Strategies One of the greatest limitations for biomarker qualification is the lack of clear guidance on biomarker development and validation by regulatory agencies. Although definitions and frameworks/examples have been provided, no clear guidance is available on ideal study designs, a clinically acceptable coefficient of variation, or other metrics used to gain approval. In Table 2, we have summarized operating properties that require assessment for the development of a surrogate biomarker for use in clinical trials and clinical practice and areas in need of clarification from both regulatory agencies and disease-specific societies. FC remains to be fully validated as a surrogate biomarker in IBD. A formal assessment of its ability to replace endoscopy in a treat-totarget monitoring and endpoint algorithm is required to understand if biomarkers can serve as endpoints as opposed to adjunctive monitoring tools.

Supplementary Material Note: To access the supplementary material accompanying this article, visit the online version of Gastroenterology at www.gastrojournal.org, and at https://doi.org/10.1053/ j.gastro.2019.06.018.

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Received February 28, 2019. Accepted June 13, 2019. Reprint requests Address requests for reprints to: Parambir S. Dulai, MD, University of California at San Diego, Division of Gastroenterology, 9500 Gilman Drive, La Jolla, Califorinia 92093. e-mail: [email protected]. Acknowledgement Author contributions: Parambir S. Dulai: guarantor of article, review of literature, drafting of the manuscript. All authors: critical review and editing of the manuscript, final approval of the manuscript. Conflicts of interest These authors disclose the following: Parambir S. Dulai has received research support from AbbVie, Pfizer, Janssen, Takeda, Bulhmman, Alpco, and Polymedco; consulting or honoraria from Janssen and Takeda; and travel support from Janssen and Takeda. Laurent Peyrin-Biroulet has received honoraria from Merck, AbbVie, Janssen, Genentech, Ferring, Tillots, Vifor, Pharmacosmos, Celltrion, Takeda, Biogaran, Boerhinger Ingelheim, Lilly, Pfizer, Index Pharmaceuticals, Amgen, Sandoz, Celgene, Biogen, Samsung Bioepis, Alma, Sterna, Nestlé, Enterome, Mylan, and HAC-Pharma. Silvio Danese reports consultancy fees from AbbVie, Allergan, Amgen, AstraZeneca, Biogen, Boehringer Ingelheim, Celgene, Celltrion, Ferring Pharmaceuticals, Gilead, Hospira, Janssen, Johnson & Johnson, MSD, Mundipharma, Pfizer, Roche, Sandoz, Takeda, TiGenix, UCB, and Vifor. Bruce E. Sands has received consulting fees and research grants from AbbVie, Pfizer, Amgen, Bristol-Myers Squibb, Celgene, Janssen, and Takeda and has received consulting fees from 4D Pharma, Boehringer Ingelheim, Arena Pharmaceuticals, Forward Pharma, Gilead, Immune Pharmaceuticals, Lilly, Otsuka, Synergy Pharmaceuticals, Theravance, Receptos, TiGenix, TopiVert Pharma, MedImmune, Allergan, UCB Pharma, EnGene, Target PharmaSolutions, Lycera, Lyndra, Vivelix Pharmaceuticals, and Oppilan Pharma. Axel Dignass served as a consultant for AbbVie, Celgene, MSD, Roche, Sandoz/Hexal, Pfizer, Takeda, Tillots, Janssen, and Vifor; received payment for development of educational presentations from Ferring and Tillots; received speaker fees from Falk Foundation, AbbVie, Ferring, Pfizer, Janssen, MSD, Vifor, Celgene, Tillots and Takeda; received manuscript fees from Thieme and Wiley; and received research grants from Institut für Gemeinwohl, Deutsche Morbus Crohn und Colitis ulcerosa Vereinigung and Stiftung Leben mit Krebs. Dan Turner received consultation fees, research grants, royalties, or honoraria from Janssen, Pfizer, Hospital for Sick Children, Ferring, AstraZeneca, AbbVie, Takeda, Boehringer Ingelheim, Biogen, Atlantic Health, Shire, Celgene, and Lilly. Gerassimos Mantzaris is an advisory board member for AbbVie, Astellas, Celgene, Danone, Ferirng, Genesis, Hospira, Janssen, Millennium Pharmaceuticals, MSD, Otsuka, Pharmacosmos, Pfizer, Sandoz, Takeda, and UCB; is a speaker for AbbVie, Angelini, Astellas, Danone, Falk Pharma, Ferring, Galenica, Hospira, Janssen, MSD, Omega Pharma, and Takeda; is a consultant for MSD and Takeda; and provides research support for AbbVie, Galenica, Genesis, Menarini Group, MSD, and Pharmathen. Walter Reinisch has served as a speaker for

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Abbott Laboratories, AbbVie, Aesca, Aptalis, Astellas, Centocor, Celltrion, Danone Austria, Elan, Falk Pharma, Ferring, Immundiagnostik, Mitsubishi Tanabe Pharma Corporation, MSD, Otsuka, PDL, Pharmacosmos, PLS Education, Schering-Plough, Shire, Takeda, Therakos, Vifor, and Yakult; as a consultant for Abbott Laboratories, AbbVie, Aesca, Amgen, AM Pharma, AOP Orphan, Arena Pharmaceuticals, Astellas, AstraZeneca, Avaxia, Roland Berger, Bioclinica, Biogen IDEC, Boehringer Ingelheim, Bristol-Myers Squibb, Cellerix, Chemocentryx, Celgene, Centocor, Celltrion, Covance, Danone Austria, Elan, Eli Lilly, Ernest & Young, Falk Pharma, Ferring, Galapagos, Genentech, Gilead, Grünenthal, ICON, Index Pharma, Inova, Janssen, Johnson & Johnson, Kyowa Hakko Kirin Pharma, Lipid Therapeutics, LivaNova, Mallinckrodt, Medahead, MedImmune, Millenium, Mitsubishi Tanabe Pharma Corporation, MSD, Nash Pharmaceuticals, Nestle, Nippon Kayaku, Novartis, Ocera, Otsuka, Parexel, PDL, Periconsulting, Pharmacosmos, Philip Morris Institute, Pfizer, Procter & Gamble, Prometheus, Protagonist, Provention, Robarts Clinical Trial, Sandoz, Schering-Plough, Second Genome, Seres Therapeutics, Setpointmedical, Sigmoid, Takeda, Therakos, Tigenix, UCB, Vifor, Zealand, Zyngenia, and 4SC; as an advisory board member for Abbott Laboratories, AbbVie, Aesca, Amgen, AM Pharma, Astellas, AstraZeneca, Avaxia, Biogen IDEC, Boehringer Ingelheim, Bristol-Myers Squibb, Cellerix, Chemocentryx, Celgene, Centocor, Celltrion, Danone Austria, Elan, Ferring, Galapagos, Genentech, Grünenthal, Inova, Janssen, Johnson & Johnson, Kyowa Hakko Kirin Pharma, Lipid Therapeutics, MedImmune, Millenium, Mitsubishi Tanabe Pharma Corporation, MSD, Nestle, Novartis, Ocera, Otsuka, PDL, Pharmacosmos, Pfizer, Procter & Gamble, Prometheus, Sandoz, Schering-Plough, Second Genome, SetPoint Medical, Takeda, Therakos, Tigenix, UCB, Zealand, Zyngenia, and 4SC; and has received research funding from Abbott Laboratories, AbbVie, Aesca, Centocor, Falk Pharma GmbH, Immundiagnsotik, and MSD. William J. Sandborn reports research grants from Atlantic Healthcare Limited, Amgen, Genentech, Gilead Sciences, AbbVie, Janssen, Takeda, Lilly, and Celgene/Receptos; consulting fees from AbbVie, Allergan, Amgen, Arena Pharmaceuticals, Avexegen Therapeutics, BeiGene, Boehringer Ingelheim, Celgene, Celltrion, Conatus, Cosmo, Escalier Biosciences, Ferring, Forbion, Genentech, Gilead Sciences, Gossamer Bio, Incyte, Janssen, Kyowa Kirin Pharmaceutical Research, Landos Biopharma, Lilly, Oppilan Pharma, Otsuka, Pfizer, Precision IBD, Progenity, Prometheus Q6 Laboratories, Reistone, Ritter Pharmaceuticals, Robarts Clinical Trials (owned by Health Academic Research Trust, HART), Series Therapeutics, Shire, Sienna Biopharmaceuticals, Sigmoid Biotechnologies, Sterna Biologicals, Sublimity Therapeutics, Takeda, Theravance Biopharma, Tigenix, Tillotts Pharma, UCB Pharma, Ventyx Biosciences, Vimalan Biosciences, and Vivelix Pharmaceuticals; and stock or stock options from BeiGene, Escalier Biosciences, Gossamer Bio, Oppilan Pharma, Precision IBD, Progenity, Ritter Pharmaceuticals, Ventyx Biosciences, Vimalan Biosciences; his spouse has relationships with Opthotech (consultant, stock options), Progenity (consultant, stock), Oppilan Pharma (employee, stock options), Escalier Biosciences (employee, stock options), Precision IBD (employee, stock options), Ventyx Biosciences (employee, stock options), and Vimalan Biosciences (employee, stock options). The remaining authors disclose no conflicts.

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Supplementary Table 1.Technical Considerations and Reliability of Fecal Calprotectin Key findings and observations

Whitehead et al28

Bülhmann (Amherst, NH) assay reported 3.8 times higher FC concentrations than Immundiagnstik (Bensheim, Germany) and Eurospital (Trieste, Italy). Commercial extraction devices led to a 7.8%–28.1% underrecovery of FC compared with manual weighting. A 12% decline in FC levels was seen within 24 hours of stool collection, irrespective of storage temperature. Samples were progressively more unstable with longer storage times at room temperature. Within- and between-subject FC variability resulted in a reference change value of nearly 100%.a Low-quality agreement between assays necessitated different numerical values between assays for clinical cutoffs. Correlation between POC FC testing kit and ELISA was better at clinically meaningful lower ranges (250 mg/g). There was strong correlation between POC FC testing kit and laboratory assay (correlation coefficient, 0.89); however, coefficient of variation was only 2.3%–5.5% for laboratory assay and 4.8%–26.6% for POC FC. POC FC was in agreement with alternative laboratory-based testing, but only at lower ranges (< 500 mg/g); however, the predetermined limits of agreement were wide, at ±100 mg/g. Interkit/interassay variability in absolutely values was observed; however, the diagnostic sensitivity of FC was not affected by the interkit/interassay variability in absolute values. There was variability across assays in diagnostic accuracy and correlation with disease activity measures. A 52% median individual coefficient of variation was found for samples collected during the same day, and FC values were significantly influenced by stool frequency. A median coefficient of variation of 40% (5%–114%) was found, with a median range of variation for FC of 3887 (69–9946 mg/kg). The first morning sample appeared to be most consistent in obtaining the highest and lowest within-day FC values. Low variability in FC was found across samples collected during different days (ICC, 0.84; 95% CI, 0.79–0.89) in clinical remission. An 8%–23% intra-stool variability was found in FC, which was influenced by the timing of collection or the cutoff used to define a positive FC result. A 13%–26% inter-stool variability was found throughout the day depending on the FC cutoff used to define a positive result. There was substantial variability in agreement across platforms/assays. FC reductions were not observed until week 2 of therapy, whereas symptoms decreased by day 3, and a decrease in symptoms more accurately predicted ultimate MH. Within-day variabilities in FC were very wide within the first 2 weeks of therapy and may have caused this inability of FC to respond to changes in health status. Two morning samples with FC cutoff > 250 mg/g provided modest reliability.

Padoan et al29

Heida et al33 Whitehead et al34 Jang et al35 Lasson et al36 Calafat et al37 Naismith et al38 Du et al39 Kittanakom et al40 Toyonaga et al41

Kristensen et al42

Q23 Q22

Q24

CD, Crohn’s disease; CI, confidence interval; ELISA, enzyme-linked immunosorbent assay; FC, fecal calprotectin; ICC, intraclass correlation; MH, mucosal healing; POC, point of care. a Reference change values provide objective tools for assessment of the significance of differences in serial results from an individual.73

IOIBD: Biomarkers in IBD

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Oyaert M. et al30 Rodriguez et al31 Hejl et al32

2019

Reference

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