HLA-DQA1*05 carriage associated with development of anti-drug antibodies to infliximab and adalimumab in patients with Crohn's Disease

Anti-tumor necrosis factor (anti-TNF) therapies are the most widely used biologic drugs for treating immune-mediated diseases, but repeated administration can induce the formation of anti-drug antibodies. The ability to identify patients at increased risk for development of anti-drug antibodies would facilitate selection of therapy and use of preventative strategies.This article is freely available via Open Access. Click on Publisher URL to access the full-text

Mechanisms and management of loss of response to anti-TNF therapy for patients with Crohn's disease: 3-year data from the prospective, multicentre PANTS cohort study

This is the final version. Available from Elsevier via the DOI in this record. Background We sought to report the effectiveness of infliximab and adalimumab over the first 3 years of treatment and to define the factors that predict anti-TNF treatment failure and the strategies that prevent or mitigate loss of response. Methods Personalised Anti-TNF therapy in Crohn’s disease (PANTS) is a UK-wide, multicentre, prospective observational cohort study reporting the rates of effectiveness of infliximab and adalimumab in anti-TNF-naive patients with active luminal Crohn’s disease aged 6 years and older. At the end of the first year, sites were invited to enrol participants still receiving study drug into the 2-year PANTS-extension study. We estimated rates of remission across the whole cohort at the end of years 1, 2, and 3 of the study using a modified survival technique with permutation testing. Multivariable regression and survival analyses were used to identify factors associated with loss of response in patients who had initially responded to anti-TNF therapy and with immunogenicity. Loss of response was defined in patients who initially responded to anti-TNF therapy at the end of induction and who subsequently developed symptomatic activity that warranted an escalation of steroid, immunomodulatory, or anti-TNF therapy, resectional surgery, or exit from study due to treatment failure. This study was registered with ClinicalTrials.gov, NCT03088449, and is now complete. Findings Between March 19, 2014, and Sept 21, 2017, 389 (41%) of 955 patients treated with infliximab and 209 (32%) of 655 treated with adalimumab in the PANTS study entered the PANTS-extension study (median age 32·5 years [IQR 22·1–46·8], 307 [51%] of 598 were female, and 291 [49%] were male). The estimated proportion of patients in remission at the end of years 1, 2, and 3 were, for infliximab 40·2% (95% CI 36·7–43·7), 34·4% (29·9–39·0), and 34·7% (29·8–39·5), and for adalimumab 35·9% (95% CI 31·2–40·5), 32·9% (26·8–39·2), and 28·9% (21·9–36·3), respectively. Optimal drug concentrations at week 14 to predict remission at any later timepoints were 6·1–10·0 mg/L for infliximab and 10·1–12·0 mg/L for adalimumab. After excluding patients who had primary non-response, the estimated proportions of patients who had loss of response by years 1, 2, and 3 were, for infliximab 34·4% (95% CI 30·4–38·2), 54·5% (49·4–59·0), and 60·0% (54·1–65·2), and for adalimumab 32·1% (26·7–37·1), 47·2% (40·2–53·4), and 68·4% (50·9–79·7), respectively. In multivariable analysis, loss of response at year 2 and 3 for patients treated with infliximab and adalimumab was predicted by low anti-TNF drug concentrations at week 14 (infliximab: hazard ratio [HR] for each ten-fold increase in drug concentration 0·45 [95% CI 0·30–0·67], adalimumab: 0·39 [0·22–0·70]). For patients treated with infliximab, loss of response was also associated with female sex (vs male sex; HR 1·47 [95% CI 1·11–1·95]), obesity (vs not obese 1·62 [1·08–2·42]), baseline white cell count (1·06 [1·02–1·11) per 1 × 10⁹ increase in cells per L), and thiopurine dose quartile. Among patients treated with adalimumab, carriage of the HLA-DQA1*05 risk variant was associated with loss of response (HR 1·95 [95% CI 1·17–3·25]). By the end of year 3, the estimated proportion of patients who developed anti-drug antibodies associated with undetectable drug concentrations was 44·0% (95% CI 38·1–49·4) among patients treated with infliximab and 20·3% (13·8–26·2) among those treated with adalimumab. The development of antidrug antibodies associated with undetectable drug concentrations was significantly associated with treatment without concomitant immunomodulator use for both groups (HR for immunomodulator use: infliximab 0·40 [95% CI 0·31–0·52], adalimumab 0·42 [95% CI 0·24–0·75]), and with carriage of HLA-DQA1*05 risk variant for infliximab (HR for carriage of risk variant: infliximab 1·46 [1·13–1·88]) but not for adalimumab (HR 1·60 [0·92–2·77]). Concomitant use of an immunomodulator before or on the day of starting infliximab was associated with increased time without the development of anti-drug antibodies associated with undetectable drug concentrations compared with use of infliximab alone (HR 2·87 [95% CI 2·20–3·74]) or introduction of an immunomodulator after anti-TNF initiation (1·70 [1·11–2·59]). In years 2 and 3, 16 (4%) of 389 patients treated with infliximab and 11 (5%) of 209 treated with adalimumab had adverse events leading to treatment withdrawal. Nine (2%) patients treated with infliximab and two (1%) of those treated with adalimumab had serious infections in years 2 and 3. Interpretation Only around a third of patients with active luminal Crohn’s disease treated with an anti-TNF drug were in remission at the end of 3 years of treatment. Low drug concentrations at the end of the induction period predict loss of response by year 3 of treatment, suggesting higher drug concentrations during the first year of treatment, particularly during induction, might lead to better long-term outcomes. Anti-drug antibodies associated with undetectable drug concentrations of infliximab, but not adalimumab, can be predicted by carriage of HLA-DQA1*05 and mitigated by concomitant immunomodulator use for both drugs.Guts UKCrohn’s and Colitis UKCure Crohn’s ColitisAbbVieMerck Sharp and DohmeNapp PharmaceuticalsPfizerCelltrion Healthcar

Associations Between the Smoking-relatedness of a Cancer Type, Cessation Attitudes and Beliefs, and Future Abstinence Among Recent Quitters

Objective: Smoking after a diagnosis of cancer can negatively impact treatment outcomes and quality of life. It is important that patients quit smoking and remain abstinent regardless of cancer type. Some cancer types (eg, lung) have stronger links to smoking as a cause than do others (eg, colorectal). The aims of this study were to (1) assess associations between smoking-relatedness of the cancer type with beliefs and attitudes concerning smoking abstinence (eg, confidence, self-efficacy), and (2) assess these variables as predictors of future abstinence. Methods: In this secondary analysis, cancer patients (N = 357) who quit smoking within the previous 90 days were assigned a code of 3, 2, or 1 according to the cancer type\u27s level of smoking-relatedness: Very related (n = 134, thoracic and head and neck), Somewhat related (n = 93, acute myeloid leukemia, bladder, cervix, colorectal, esophageal, kidney, liver, pancreas, and stomach), and Unlikely related (n = 137, all other cancer types). Results: Smoking-relatedness was positively associated with plan to stay smoke-free, maximum confidence in being smoke-free in 6 months, higher abstinence self-efficacy, and lower expected difficulty in staying smoke-free. Each of the 4 beliefs and attitude variables predicted abstinence 2 months later. Smoking-relatedness also predicted abstinence in a univariate model, but not in a multivariable model with the belief and attitude variables. Using backwards stepwise procedures, the final model included plan to stay smoke-free, confidence in being smoke-free, and abstinence self-efficacy. Conclusion: These results are consistent with our conceptualization of cessation motivation differing by smoking-relatedness of the cancer type and predicting future abstinence

Associations Between the Smoking-relatedness of a Cancer Type, Cessation Attitudes and Beliefs, and Future Abstinence Among Recent Quitters

Objective: Smoking after a diagnosis of cancer can negatively impact treatment outcomes and quality of life. It is important that patients quit smoking and remain abstinent regardless of cancer type. Some cancer types (eg, lung) have stronger links to smoking as a cause than do others (eg, colorectal). The aims of this study were to (1) assess associations between smoking-relatedness of the cancer type with beliefs and attitudes concerning smoking abstinence (eg, confidence, self-efficacy), and (2) assess these variables as predictors of future abstinence. Methods: In this secondary analysis, cancer patients (N = 357) who quit smoking within the previous 90 days were assigned a code of 3, 2, or 1 according to the cancer type\u27s level of smoking-relatedness: Very related (n = 134, thoracic and head and neck), Somewhat related (n = 93, acute myeloid leukemia, bladder, cervix, colorectal, esophageal, kidney, liver, pancreas, and stomach), and Unlikely related (n = 137, all other cancer types). Results: Smoking-relatedness was positively associated with plan to stay smoke-free, maximum confidence in being smoke-free in 6 months, higher abstinence self-efficacy, and lower expected difficulty in staying smoke-free. Each of the 4 beliefs and attitude variables predicted abstinence 2 months later. Smoking-relatedness also predicted abstinence in a univariate model, but not in a multivariable model with the belief and attitude variables. Using backwards stepwise procedures, the final model included plan to stay smoke-free, confidence in being smoke-free, and abstinence self-efficacy. Conclusion: These results are consistent with our conceptualization of cessation motivation differing by smoking-relatedness of the cancer type and predicting future abstinence

Does smoking abstinence predict cancer patients' quality of life over time?

Objective: Smoking cessation improves quality of life (QOL) in the general population. However, there is limited information on the role of smoking status on QOL among cancer patients. Moreover, previous studies tended to analyze smoking status dichotomously and at a single point in time, potentially reducing the strength of the relation between smoking cessation and QOL. This study examined the association of smoking abstinence and QOL over time, including depression, pain, and fatigue in patients with a wide variety of cancers. Methods: Participants were 332 cancer patients (eg, gynecologic, breast, thoracic, head and neck, and genitourinary) who had been abstinent for at least 24 hours. Days abstinent and QOL were assessed at baseline and 2, 6, and 12 months later. Latent growth curve models examined if days abstinent was associated with QOL at each assessment. Baseline demographics (eg, sex and income) and smoking history variables (eg, nicotine dependence) were used as time-invariant covariates. Results: The final model for each QOL component had good-to-excellent fit. More days abstinent was associated with lower depression at all follow-ups and with lower fatigue at 12 months but was not associated with pain. Conclusions: QOL was better among patients who quit smoking for longer periods. Findings suggest different timelines, with smoking abstinence most immediately associated with lower depression, followed by lower fatigue. Although pain decreased over time, it was not associated with length of smoking abstinence. Results reinforce the relationship between sustained smoking cessation and QOL, which should be communicated to patients

Does Smoking Abstinence Predict Cancer Patients\u27 Quality of Life Over Time?

Objective: Smoking cessation improves quality of life (QOL) in the general population. However, there is limited information on the role of smoking status on QOL among cancer patients. Moreover, previous studies tended to analyze smoking status dichotomously and at a single point in time, potentially reducing the strength of the relation between smoking cessation and QOL. This study examined the association of smoking abstinence and QOL over time, including depression, pain, and fatigue in patients with a wide variety of cancers. Methods: Participants were 332 cancer patients (eg, gynecologic, breast, thoracic, head and neck, and genitourinary) who had been abstinent for at least 24 hours. Days abstinent and QOL were assessed at baseline and 2, 6, and 12 months later. Latent growth curve models examined if days abstinent was associated with QOL at each assessment. Baseline demographics (eg, sex and income) and smoking history variables (eg, nicotine dependence) were used as time-invariant covariates. Results: The final model for each QOL component had good-to-excellent fit. More days abstinent was associated with lower depression at all follow-ups and with lower fatigue at 12 months but was not associated with pain. Conclusions: QOL was better among patients who quit smoking for longer periods. Findings suggest different timelines, with smoking abstinence most immediately associated with lower depression, followed by lower fatigue. Although pain decreased over time, it was not associated with length of smoking abstinence. Results reinforce the relationship between sustained smoking cessation and QOL, which should be communicated to patients

Smoking status predicts cancer patients' quality of life over time

Background Previous studies indicate that quitting smoking significantly improves health-related quality of life (QOL) in patients with lung and head and neck cancer. However, few prospective studies have investigated the role of smoking status on QOL across patients diagnosed with a wide range of cancers. The aim of the present study was to examine quality of life (depression, pain, and fatigue) changes over time as a function of smoking status. Methods Participants were 351 cancer patients (e.g., gynecological, breast, thoracic, head and neck, genitourinary, hematological, cutaneous) who reported smoking abstinence within the previous 120 days. Smoking status and QOL (depression, pain severity, fatigue severity, and fatigue interference) were assessed at baseline, 2, 6, and 12 month follow-ups. Within a Structural Equation Modeling (SEM) framework, growth curve models with smoking status as a time varying covariate were employed to examine the effect of smoking status change in QOL measures over time. Baseline demographics (e.g., sex, income) and smoking history (e.g., nicotine dependence) were controlled. Results Overall, models with both time-varying covariates (smoking status) and time-invariant covariates (demographics, nicotine dependence) were good-to-excellent fits with the data. Smoking status had a main effect and an interaction with time upon depression and pain severity. For fatigue severity and fatigue interference, smoking status interacted with time, i.e., smoking abstinence at the 6 and 12 months follow-ups were associated with lower fatigue scores across the estimated growth curve. Conclusions These results extend previous findings showing that QOL improves in cancer patients who quit smoking. Specifically, patients who quit smoking experience a greater reduction in depression and pain levels at all time points, and the reduction increases over time. In the case of fatigue, the results suggest that patients experience the greatest improvement with longer (≥ 4 months) abstinence

Social Media and Journalistic Independence

The Abstinence-Related Motivational Engagement (ARME) scale was developed to assess motivation to remain abstinent after a smoking cessation attempt. The ARME demonstrated reliability and validity among a small sample of ex-smokers. This study expands the psychometric evaluation of the ARME and tests the ARME as a predictor of smoking status among a sample of participants quitting smoking. The parent trial tested the efficacy of a self-help smoking cessation intervention (N = 1874), with assessments every 6 months. Internal consistency and factor structure of the ARME was evaluated at each assessment to confirm use of the measure as designed. Discriminant validity was assessed by comparing the ARME to the Situation-specific Abstinence Self-Efficacy (SSE) scale via inter-correlations and prediction of future smoking status. Finally, the trajectories of both the ARME and SSE were compared among continuous abstainers and continuous smokers. A single-factor structure was observed at each assessment. Cronbach's alphas ranged from 0.88-0.91 for the total sample. Correlations between the ARME and the SSE ranged from 0.38-0.47 (ps 0.05) among abstainers. Among current smokers, the ARME and SSE were independent positive predictors of subsequent abstinence (AORs 1.28-2.29, ps <0.001). For those currently abstinent, only the SSE predicted subsequent abstinence (AORs 1.69-2.60, ps <0.05). GEE analyses showed different trajectories for the two measures, as well as between abstainers and smokers. In conclusion, the ARME is a reliable, valid measure with unique predictive utility for current smokers and a distinct trajectory among those who have successfully quit