Effect of Obesity on Risk of Hospitalization, Surgery, and Serious Infection in Biologic-Treated Patients With Inflammatory Bowel Diseases: A CA-IBD Cohort Study : Official journal of the American College of Gastroenterology | ACG

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ARTICLE: INFLAMMATORY BOWEL DISEASE

Effect of Obesity on Risk of Hospitalization, Surgery, and Serious Infection in Biologic-Treated Patients With Inflammatory Bowel Diseases: A CA-IBD Cohort Study

Gu, Phillip MD1; Luo, Jiyu MS2; Kim, Jihoon MS3; Paul, Paulina MS3; Limketkai, Berkeley MD, PhD4; Sauk, Jenny S. MD4; Park, Sunhee MD5; Parekh, Nimisha MD5; Zheng, Kai MD6; Rudrapatna, Vivek MD, PhD7; Syal, Gaurav MD, MHDS1; Ha, Christina MD1; McGovern, Dermot P. MD, PhD1; Melmed, Gil Y. MD, MS1; Fleshner, Phillip MD8; Eisenstein, Samuel MD9; Ramamoorthy, Sonia MD9; Dulai, Parambir S. MD10; Boland, Brigid S. MD10; Grunvald, Eduardo MD11; Mahadevan, Uma MD7; Ohno-Machado, Lucila MD, PhD3; Sandborn, William J. MD10; Singh, Siddharth MD, MS3,10

Author Information
The American Journal of Gastroenterology 117(10):p 1639-1647, October 2022. | DOI: 10.14309/ajg.0000000000001855

Abstract

INTRODUCTION

Inflammatory bowel diseases (IBD) are chronic immune-mediated conditions conventionally associated with cachexia and malnutrition, but contemporary trends show the prevalence of obesity is growing among patients with IBD, making it an increasingly important consideration for IBD management (1, 2). Approximately 15%–45% of patients with IBD are obese, and an additional 20%–40% are overweight (3). Obesity, particularly visceral adiposity, is proposed to negatively affect IBD through increased adipose tissue production of proinflammatory adipokines, chemokines, and cytokines, such as tumor necrosis factor (TNF)-α and interleukin-6 (4–6). As such, the increased systemic burden of inflammation and unfavorable pharmacokinetics of biologic agents due to obesity may increase the risk for adverse outcomes such as disease complications, poor treatment response, and infections (3,7,8).

Despite the proinflammatory effect of obesity, its effect on IBD disease course is variable. Obesity has been associated with inferior quality of life and higher healthcare resource utilization (9,10). Population pharmacokinetic studies of available biologic agents have consistently shown that increased body mass is associated with increased drug clearance and lower trough concentrations (11–13). However, in clinical studies, obesity has been inconsistently associated with inferior therapeutic response (14–16). Many previous studies were retrospective single-center cohorts limited by small sample sizes and low event rates. Recent large database studies use administrative claims that rely on diagnostic codes for the diagnosis of obesity, resulting in misclassification. In addition, there is limited data defining the effect of obesity on treatment-related complications, particularly risk of serious infections (17). Thus, clarifying the effect of obesity on treatment outcomes and risk of complications is critical for improving IBD management.

To further characterize the effect of obesity on adverse outcomes in IBD, we aim to evaluate the association between obesity and risk of hospitalization, surgery, and serious infections in a large, multicenter, electronic health record (EHR)-based cohort of biologic-treated patients with IBD.

METHODS

Data source

We created a multicenter EHR-based cohort of patients with IBD seen and followed up at 5 health systems in California (UC San Diego, UC Los Angeles, UC Irvine, UC San Francisco, and Cedars-Sinai Medical Center), using the PCORnet Common Data Model. The infrastructure for this existed through patient-centered SCAlable National Network for Effectiveness Research, one of 13 clinical data research networks previously funded by Patient-Centered Outcomes Research Institute. Patient-centered SCAlable National Network for Effectiveness Research (18,19) is a federated network that uses a distributed, service-oriented architecture to integrate data from existing networks, designed to improve our capacity to conduct comparative effectiveness research. To improve semantic interoperability and facilitate data harmonization, all data had already been transformed into the validated PCORnet common data model (version 3.1), which includes demographics, diagnosis and procedures codes, medications, laboratory data, and vital parameters.

We identified patients with IBD from EHR, based on the following criteria: (i) 2 disease diagnostic codes (Chrohn's disease [CD]: ICD-9555.x or ICD-10 K50; ulcerative colitis [UC]: ICD-9556.x or ICD-10 K51; 1 of these codes may have come from the ‟Problem List” field in the EHR) from an ambulatory visit encounter, (ii) 1 disease diagnostic code from an inpatient hospitalization, or (iii) 1 disease diagnostic code from an ambulatory visit encounter, along with a prescription for an IBD-related medication (mesalamine/sulfasalazine, azathioprine/6-mercaptopurine, methotrexate, infliximab, adalimumab, certolizumab pegol, golimumab, vedolizumab, or ustekinumab). These validated criteria have been shown to have >80% sensitivity and >90% specificity, with a positive predictive value of >90% (20–22).

Study population

From this cohort, we included adult patients (aged 18 years or older) who were newly prescribed biologic agents (TNF-α antagonists, vedolizumab, or ustekinumab) (no previous prescription of same class of medication in the preceding 12 months with ongoing healthcare contact defined as at least 1 office or inpatient visit in the health system during this period) between January 1, 2010, and June 30, 2017, those who had a 1-year follow-up within the health system, and those in conditions where weight and height (to allow estimation of body mass index [BMI]) were recorded within 3 months of initiation of a biologic agent. Once prescribed, patients were presumed to be continuously compliant for 1 year, unless a prescription for a new biologic agent was identified in the EHR, in which case the patient contributed person-time till the time of switching. Data on prescription refill claims were not available.

Exposure

Patients were classified as normal (BMI 18.5–24.9 kg/m2), overweight (BMI 25.0–29.9 kg/m2), or obese (BMI ≥30 kg/m2) based on the World Health Organization classification, at the closest time point of new biologic initiation (23). We excluded patients who were underweight during biologic initiation to avoid confounding by disease severity (BMI <18.5 kg/m2). In a secondary analysis, BMI was also analyzed as a continuous variable.

Outcomes

The primary outcomes of interest were risk of all-cause hospitalization and IBD-related abdomino-pelvic surgery (based on common procedural terminology codes). A secondary outcome of interest was risk of serious infections (defined as infections requiring hospitalization, based on international classification of diseases (ICD)-9 or ICD-10 principal discharge diagnosis of infections of the respiratory tract, skin and soft tissue, genitourinary tract, gastrointestinal tract, central nervous system, and septicemia/sepsis) (24,25). We focused on infections requiring hospitalizations because these infections are severe and more likely to have adverse outcomes that lead to therapeutic changes, including treatment discontinuation. In addition, there is considerably more heterogeneity in the severity of outpatient infections, resulting in variable clinical implications when considering biologic therapy.

Covariates

We collected baseline covariates (during biologic start or in the preceding 12 months) including demographic characteristics (age, sex, race, and ethnicity); disease and treatment characteristics, including IBD phenotype (CD or UC), recent previous biologic prescription (in a 12-month baseline period), previous and/or concomitant prescription for immunomodulators (including azathioprine, 6-mercaptopurine, or methotrexate), corticosteroids, and opiates; elevated C-reactive protein (>5 mg/L) and low albumin (<3.5 g/dL) during biologic initiation; and patterns of healthcare utilization in the preceding 12 months, including comorbidity burden measured by Elixhauser index for EHR (26), abdominal surgery, hospitalization, and serious infection. We did not have access to patients' unstructured clinic notes or endoscopy reports.

Statistical analyses

We used descriptive statistics to compare baseline demographic, disease, and treatment characteristics among patients with normal BMI, overweight, and obesity. Categorical variables were expressed as percentages and continuous variables as mean values and SD. We used the Kruskal-Wallis test and analysis of variance (ANOVA) to compare categorical and continuous variables among the 3 groups, respectively.

To evaluate the association between obesity and risk of all-cause hospitalization, IBD-related surgery, or serious infection, we performed a univariable survival analysis using the Kaplan-Meier curves and log-rank tests, followed by Cox proportional hazard analysis adjusting for age, sex, ethnicity, IBD phenotype, Elixhauser index (≥2 vs <2), abnormal baseline albumin and/or C-reactive protein (CRP), current and previous biologic exposure, concomitant medication exposure (immunomodulator, steroid, and opioids), previous abdominal surgery, previous hospitalization, and previous serious infection. Similar analysis was performed using BMI as a continuous exposure variable (per 1 kg/m2). Stratified analysis to examine the effect of obesity in specific subgroups of patients was performed, based on IBD phenotype (patients with CD or UC) and biologic exposure type [patients treated with TNF-α antagonists vs non–TNF-α antagonists (vedolizumab or ustekinumab)].

All hypothesis testing was performed with a 2-sided P value with a statistical significance threshold <0.05. All statistical analyses were performed using R version 3.5.3 (Vienna, Austria).

RESULTS

Patient characteristics

We included 3,038 patients with IBD (31.1% UC), of whom 28.2% (n = 858) were overweight and 13.7% (n = 416) were obese; 4.5% patients (n = 138) had class II (BMI 35–39.9 kg/m2) or III obesity (BMI ≥ 40 kg/m2). Most patients were new users of TNF-α antagonists (76.3%, n = 2,319) (Table 1). Overall, patients with obesity were older (P < 0.001), of Hispanic ethnicity (P = 0.013), had higher burden of comorbidities (P = 0.001), and were more likely to have elevated CRP at baseline (P = 0.003). There were no differences among patients who were obese vs those who were nonobese regarding IBD type (P = 0.08), class of biologic prescribed (P = 0.583), previous surgery (P = 0.796), or previous biologic exposure (P = 0.358).

T1
Table 1.:
Baseline characteristics between biologic-treated patients with IBD with normal BMI, overweight, and obesity (total n = 3,038)

All-cause hospitalization

On a follow-up, 22.9% (n = 697) required hospitalization within 1 year of new biologic start. On univariable analysis, 1-year risk of all-cause hospitalization was comparable among patients with normal BMI (23.4%), overweight (21.8%), and obesity (23.3%) (Figure 1a, P = 0.69). On Cox proportional hazard analysis, obesity (adjusted hazard ratio [aHR], 0.90; 95% confidence interval [CI], 0.72–1.13) and overweight status (aHR, 0.91; 95% CI, 0.76–1.08) were not associated with an increased risk of hospitalization when compared with normal BMI. When analyzed as a continuous variable, BMI (per 1 kg/m2) was associated with a lower risk of hospitalization (aHR, 0.98; 95% CI, 0.97–1.00; P = 0.044). Other independent risk factors for hospitalization included Hispanic ethnicity, higher burden of comorbidities, concomitant opiate use, concomitant corticosteroid use, previous all-cause hospitalization, and previous serious infection within 1 year before new biologic start (Table 2).

F1
Figure 1.:
The Kaplan-Meier curves for risk of (a) all-cause hospitalization, (b) IBD-related surgery, and (c) serious infections in patients with IBD and obesity vs overweight vs normal BMI within a year of starting a new biologic agent. P values are from log-rank tests for curve comparisons. IBD, inflammatory bowel diseases.
T2
Table 2.:
Multivariable Cox proportional hazard analyses evaluating risk factors for all-cause hospitalization, IBD-related surgery, and serious infections in patients with IBD within a year of starting new biologic agent

When stratified by IBD type (Figure 2a), overweight patients with CD (aHR, 0.79; 95% CI, 0.63–0.98), but not obese patients with CD (aHR, 0.9; 95% CI, 0.75–1.27) had a lower risk of hospitalization than CD patients with normal BMI. In patients with UC, neither obesity (aHR, 0.76; 95% CI, 0.48–1.18) nor overweight status (aHR, 1.22; 95% CI, 0.90–1.65) was associated with the risk of hospitalization. When stratified by biologic type, obesity was not associated with all-cause hospitalization in patients treated with TNF-α antagonists (aHR, 0.86; 95% CI, 0.66–1.12) nor non–TNF-α antagonists (aHR, 1.02; 95% CI, 0.65–1.61) (see Table, Supplementary Digital Content 1–2, https://links.lww.com/AJG/C543).

F2
Figure 2.:
Cox proportional hazards analyses. Relative to normal weight, obesity is not associated with (a) all-cause hospitalization, (b) IBD-related surgery, or (c) serious infections in patients with IBD starting new biologics when stratified by IBD phenotype. IBD, inflammatory bowel diseases.

IBD-related surgery

Within a year of starting a new biologic, 3.3% (n = 100) of patients required surgery. On univariable analysis, 1-year risk of surgery was comparable between patients with normal BMI (3.5%), those who were overweight (3.4%), and those with obesity (2.4%) (Figure 1b, P = 0.54). On Cox proportional hazard analysis, obesity (aHR, 0.62; 95% CI, 0.31–1.22) and overweight status (aHR, 1.05; 95% CI, 0.67–1.65) were not associated with the risk of IBD-related surgery when compared with normal BMI, after adjusting for demographic, clinical, and treatment characteristics. When analyzed as a continuous variable, BMI (per 1 kg/m2) was not associated with the risk of IBD-related surgery (aHR, 0.96; 95% CI, 0.92–1.01). Other independent risk factors for IBD-related surgery included Hispanic ethnicity, elevated CRP at baseline, and concomitant opiate use (Table 2).

When stratified by IBD type (Figure 2b), overweight patients with CD (aHR, 0.79; 95% CI, 0.63–0.98), but not obese patients with CD (aHR, 0.97; 95% CI, 0.75–1.27), had a lower risk of surgery when compared with patients with normal BMI. There was no association between obesity or overweight and risk of surgery in patients with UC. When stratified by biologic type, obesity was not associated with risk of surgery in patients treated with TNF-α antagonists (aHR, 0.443; 95% CI, 0.20–1.00) or non–TNF-α antagonists (aHR 1.66; 95% CI, 0.44–6.17) (see Table, Supplementary Digital Content 1–2, https://links.lww.com/AJG/C543).

Serious infection

Within 1 year of starting a biologic agent, 5.8% (n = 175) patients were hospitalized for serious infections. On univariable analysis, 1-year risk of serious infections was comparable between patients with normal BMI (5.6%), those in overweight (5.7%), and those with obesity (6.7%) (Figure 1c, P = 0.67). On Cox proportional hazard analysis, obesity (aHR, 1.11; 95% CI, 0.73–1.71) and overweight status (aHR, 0.97; 95% CI, 0.69–1.37) were not associated with the risk of serious infections compared with normal BMI, after adjusting for demographic, clinical, and treatment characteristics. When analyzed as a continuous variable, BMI (per 1 kg/m2) was not associated with the risk of serious infections (aHR, 1.00; 95% CI, 0.97–1.02). Other independent risk factors for serious infections in biologic-treated patients with IBD included higher burden of comorbidities, concomitant opiate use, and previous all-cause and infection-related hospitalization (Table 2).

On stratified analysis (Figure 2c), patients with obesity or overweight were not associated with increase in risk of serious infections in patients with CD or UC or in patients treated with TNF-α antagonists (aHR, 1.23; 95% CI, 0.77–1.93) or non–TNF-α antagonists (aHR, 0.50; 95% CI, 0.11–2.24) (see Table, Supplementary Digital Content 1–2, https://links.lww.com/AJG/C543).

DISCUSSION

In this large, multicenter, EHR-based cohort study of more than 3,000 patients with IBD starting new biologic therapy, of whom 14% were obese, we found obesity was not associated with risk of hospitalization, IBD-related surgery, or serious infections after adjusting for confounding factors within 1 year of initiating biologic therapy. We also confirmed previously observed risk factors independent from obesity for adverse treatment outcomes and serious infections with biologic therapy, including high burden of comorbidities, concomitant corticosteroid and opiate use, elevated CRP at baseline, and previous hospitalization (17,27). Our findings suggest obesity does not significantly affect unplanned healthcare utilization and treatment-related complications in patients with IBD starting new biologic therapy.

Our findings significantly contribute to the growing yet mixed body of evidence about the potential negative effect of obesity on disease course and treatment outcomes in IBD. Obesity is a chronic inflammatory state with increased proinflammatory cytokine, chemokine, and adipokine production from adipose expansion, resulting in an increased risk of cardiovascular, metabolic, and infectious complications. In other immune-mediated inflammatory diseases, obesity is associated with worse disease activity and poor treatment outcomes (3,14). In IBD, obesity has been associated with worse quality of life, risk of relapse, hospital readmission, and higher burden of healthcare costs (9,10). Obesity may confer inferior response to biologic therapy by promoting drug clearance through proteolysis (28) and through a ‟TNF sink” phenomenon, where increased levels of adipose tissue secreted TNF-α sequester TNF-α antagonists (3). However, clinical studies have variably shown a negative association between obesity and inferior biologic response. In addition, studies specifically evaluating the effect of obesity on weight-based vs fixed-dose biologic agents have not found differential influence on effectiveness or drug concentration levels (14,29,30). Early studies have suggested that obesity is associated with an increased need for dose escalation, hospitalization, or surgery in IBD, but these studies were limited by small sample sizes or single-center studies (29,31,32). Larger studies demonstrating higher burden of unplanned healthcare utilization in patients with obesity and IBD have relied on administrative claims codes, which can underreport obesity. Conversely, several recent meta-analyses of observational studies and randomized control trial (RCT) found that obesity did not significantly modify response to TNF-α antagonists and non–anti-TNF-⍺–targeting agents, which is consistent with our findings (14,15,33). In addition, we did not find that obesity was associated with risk of surgery. The discrepancy among studies potentially reflects the shortcomings of overall obesity measured using BMI to capture clinically meaningful adiposity. A small but growing body of literature suggests visceral adipose tissue is a potentially superior prognostic measure of adiposity and better predicts adverse outcomes in IBD (34–39). These findings warrant further investigation to better inform management decisions. Interestingly, we also noted that patients with CD and who were overweight had a lower risk for all-cause hospitalizations and IBD-related surgery compared with CD patients with normal weight. Similar nonlinear associations between BMI and mortality (i.e., obesity paradox) have been described in large epidemiologic studies in non-IBD patients (40,41). While this counter-intuitive relationship potentially supports the inaccuracies of using BMI to capture the detrimental effects of adiposity, it also poses the question whether patients with CD who are in “normal” weight experience more severe disease and different underlying metabolic physiology that precludes weight gain or causes weight loss from a previously increased BMI. This may be particularly true in CD with small bowel involvement or with CD-related complications (42). Further studies are needed to verify this finding because it may enhance patient risk stratification when making clinical decisions.

While most studies have evaluated the effect of obesity on disease course and treatment response, evidence surrounding the effect of obesity on treatment-related complications remains limited, especially risk of serious infections. In nonimmune suppressed patients, obesity significantly increases the risk for respiratory, gastrointestinal, and surgical site infections (8). Considering patients with obesity and IBD potentially require higher doses of immunosuppressives to control inflammation, understanding how obesity modifies the risk of serious infections is imperative. In patients with IBD receiving immunomodulator therapy, diabetes was independently associated with almost a 2-fold increased risk of infection (43). By contrast, a propensity score–matched cohort study of hospitalized patients with IBD found that obesity was not associated with risk of infection-related hospitalization (10). Similarly, a recent administrative claims-based study of nearly 6,000 biologic-treated IBD patients found that obesity was not associated with risk of serious infections (17). However, these studies relied on administrative claims to diagnose obesity, which is subject to misclassification. Our study strengthens the limited available data by classifying obesity using standard World Health Organization criteria based on BMI and confirms previous findings that obesity is not associated with risk of serious infections in biologic-treated patients with IBD.

Our study has several notable strengths including large sample size, high event rates, a multicenter cohort, and use of standard criteria for classifying obesity based on BMI. However, there are important limitations. First, we were not able to extract detailed disease characteristics such as disease distribution, behavior, duration, and clinical and endoscopic disease activity indexes, which may be important confounders. Second, we relied on medication prescription in EHR but cannot confirm that medications were dispensed nor confirm compliance. In a validation study of EHR prescriptions recorded using the PCORnet common data model against dispensing records, sensitivity of prescriptions in the EHR was 99.1% and 89.9% for closed integrated delivery systems and nonclosed integrated delivery systems, respectively (44). In addition, biologic dosing regimens and drug concentration levels were not readily obtainable, so it is possible that patients with obesity required higher biologic dosing to achieve similar outcomes as patients with normal BMI. Third, the recorded BMI may not reflect patients' baseline weights, which could be influenced by disease activity or prebiologic steroid use. In a previous study in an Internet-based cohort of patients with IBD, we observed that over a 12-month follow-up, 78.3%–91.2% remained in their respective BMI categories at 12 months. Among patients with change in BMI, most moved up or down 1 category; <0.5% moved up or down 2 categories (except 2% patients with baseline class II or III obesity, who had a BMI of <30 kg/m2at follow-up); hence, the likelihood of misclassification of BMI is very small (9). Fourth, outcome ascertainment was limited to events occurring in the health systems involved; events occurring at hospitals outside these health systems were not captured. Moreover, a small subset of patients may have been seen at more than 1 study site (UC health systems and/or Cedars-Sinai Medical Center) during the course of the study and may have been double-counted. Fifth, structured data elements specific to this cohort were not validated against chart review. However, the PCORnet common data model itself has been extensively implemented, quality controlled, and validated (45). Finally, we used BMI to reflect obesity, which may not be an accurate marker for adiposity. Recent evidence has suggested visceral adipose tissue (VAT) is a more accurate marker of adiposity (46) and has been associated with an increased risk of IBD-related complications and biologic response. Of note, the prevalence of obesity in our cohort is on the lower end of reported prevalence rates from the available literature. This potentially reflects the overall prevalence of obesity of California is lower than the national average in the United States. In addition, previous studies reporting an obesity prevalence of 15%–45% included all patients with IBD, and some studies suggest a milder phenotype of IBD in obese patients. Our study includes only patients with IBD who are starting a new biologic and have a more severe phenotype, which may contribute to lower observed prevalence of obesity.

In conclusion, in a large, multicenter, EHR-based cohort of biologic-treated patients with IBD, obesity was not associated with an increased risk of unplanned healthcare utilization and serious infections. Our data provide reassuring evidence that obesity does not negatively modify patients' clinical course and obesity does not increase risk of infections with biologics, suggesting early aggressive immunosuppressive therapy can be safely used if necessary. Future studies examining the effect of visceral adiposity on patient-reported and endoscopic outcomes are needed to better inform therapeutic decisions in this expanding patient population.

CONFLICTS OF INTEREST

Guarantor of the article: Siddharth Singh, MD, MS.

Specific author contributions: Study concept and design: W.J.S., L.O.-M., S.S. Acquisition, analysis and interpretation of data: P.G., J.L., P.P., J.K., B.L., J.S., S.P., N.P., K.Z., V.R., G.S., C.H., D.M., G.M., P.F., S.E., S.R., P.S.D., B.S.B., E.J.G., U.M., L.O.-M., W.J.S., S.S. Drafting of the manuscript: P.G., S.S. Critical revision of the manuscript for important intellectual content: J.L., P.P., J.K., B.L., J.S., S.P., N.P., K.Z., V.R., G.S., C.H., D.M., G.M., P.F., S.E., S.R., P.S.D., B.S.B., E.J.G., U.M., L.O.-M., W.J.S. Approval of the final manuscript: P.G., J.L., P.P., J.K., B.L., J.S., S.P., N.P., K.Z., V.R., G.S., C.H., D.M., G.M., P.F., S.E., S.R., P.S.D., B.S.B., E.J.G., U.M., L.O.-M., W.J.S., S.S.

Financial support: This project was supported by the ACG Junior Faculty Development Award and the Crohn's and Colitis Foundation Career Development Award (#404614) to S.S. S.S. is supported by NIDDK K23DK117058 and R03DK129631, Litwin Pioneers in IBD grant, and PCORI Contract CER-2020C3-21024. L.O.-M. is funded by NIH grants R01HG011066, R01HL136835, OT2OD026552, and U24LM013755. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

Potential competing interests: P.G. No conflicts of interests to disclose. J.L.: No conflicts of interests to disclose. P.P.: No conflicts of interests to disclose. J.K.: No conflicts of interests to disclose. B.L.: No conflicts of interests to disclose. J.S.S.: Consultant (CorEvitas LLC); Speaker's Bureau (Abbvie, Pfizer); Advisory Board (Prometheus). S.P.: Speaker's Bureau (AbbVie, Bristol-Myers-Squibb), Advisory board (AbbVie, Bristol-Myers-Squibb, Prometheus, Pfizer, Arena). N.P.: Consultant (Pfizer). K.Z.: No conflicts of interests to disclose. V.R.: Research support (Janssen, Alnylam). G.S.: Research support (Pfizer). C.H.: Research support (AbbVie, Pfizer, Genentech, Lilly), Speaker's Bureau (AbbVie), Advisory board (AbbVie, Janssen, Pfizer, InDex pharmaceuticals, Genentech, Lilly, Bristol-Myers-Squibb, Takeda). D.M.: Consultant (Gilead, Takeda, Pfizer, Boehringer Ingelheim, Qu Biologics, Bridge Biotherapeutics, Prometheus Biosciences Inc, and Prometheus Labs), stock (Prometheus Biosciences Inc). G.M.: Consultant (AbbVie, Arena Pharmaceuticals, Boehringer-Ingelheim, Bristol-Myers-Squibb, Entasis, Ferring, Janssen, Lilly, Medtronic, Pfizer, Samsung Bioepis, Shionogi, Takeda, Techlab), research grants (AbbVie, Pfizer). P.F.: Consultant (Takeda). S.E.: Consultant (Ethicon Surgical Robotics, Takeda), research support (Allergan). S.R.: No conflicts of interests to disclose. P.D.: Research support and/or consulting (Takeda, Janssen, Pfizer, Abbvie, Gilead, Lily, Bristol-Myers-Squibb, Novartis), stock options (DigbiHealth), licensing royalties (Precidiag). B.B.: Consultant (Bristol Myers Squibb, Takeda), Research support (Prometheus Biosciences, Gilead). E.G.: Consultant (Novo Nordisk, Currax Pharmaceuticals, Gelesis Inc); Research support (Aardvark Therapeutics). U.M.: Consultant (AbbVie, Janssen, Pfizer, Takeda, and Bristol-Myers-Squibb). L.O.-M.: No conflicts of interests to disclose. W.J.S.: has received research grants from Abbvie, Abivax, Arena Pharmaceuticals, Boehringer Ingelheim, Bristol Meyers Squibb, Genentech, Gilead Sciences, Glaxo Smith Kline, Janssen, Lilly, Pfizer, Prometheus Biosciences, Seres Therapeutics, Shire, Takeda, Theravance Biopharma; consulting fees from Abbvie, Abivax, Alfasigma, Alimentiv (previously Robarts Clinical Trials, owned by Alimentiv Health Trust), Allakos, Amgen, Arena Pharmaceuticals, AstraZeneca, Atlantic Pharmaceuticals, Beigene, Boehringer Ingelheim, Bristol Meyers Squibb, Celltrion, Clostrabio, Forbion, Galapagos, Genentech (Roche), GlaxoSmithKline, Gossamer Bio, Index Pharmaceuticals, Iota Biosciences, Janssen, Lilly, Morphic Therapeutics, Novartis, Oppilan Pharma (now Ventyx Biosciences), Pfizer, Pharm Olam, Polpharm, Progenity, Prometheus Biosciences, Protagonist Therapeutics, PTM Therapeutics, Seres Therapeutics, Shoreline Biosciences, Sublimity Therapeutics, Surrozen, Takeda, Theravance Biopharma, Vedanta Biosciences, Ventyx Biosciences, Vimalan Biosciences, Vivreon Gastrosciences, Xencor, Zealand Pharmaceuticals; stock or stock options from Allakos, BeiGene, Gossamer Bio, Oppilan Pharma (now Ventyx Biosciences), Progenity, Prometheus Biosciences, Prometheus Laboratories, Protagonists Therapeutics, Shoreline Biosciences, Ventyx Biosciences, Vimalan Biosciences, Vivreon Gastrosciences; and employee at Shoreline Biosciences. Spouse: Iveric Bio–consultant, stock options; Progenity–stock; Oppilan Pharma (now Ventyx Biosciences)–stock; Prometheus Biosciences–employee, stock, stock options; Prometheus Laboratories–stock, stock options, consultant; Ventyx Biosciences–stock, stock options; Vimalan Biosciences–stock, stock options. S.S. reports research grants from AbbVie, Janssen, and Pfizer and personal fees from Pfizer (for ad hoc grant review).

Study Highlights

WHAT IS KNOWN

  • ✓ Prevalence of obesity is increased in inflammatory bowel disease (IBD).
  • ✓ In IBD, obesity has been associated with inferior quality life and higher healthcare resource utilization.
  • ✓ Obesity is variably associated with inferior response to biologic therapy.

WHAT IS NEW HERE

  • ✓ In a large, multicenter, electronic health record–based cohort of patients with IBD who are new users of biologic agents, obesity was not associated with an increased risk of hospitalization, IBD-related surgery, and serious infections.

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