Risk of depression, suicide and psychosis with hydroxychloroquine treatment for rheumatoid arthritis: a multinational network cohort study.

OBJECTIVES: Concern has been raised in the rheumatology community regarding recent regulatory warnings that HCQ used in the coronavirus disease 2019 pandemic could cause acute psychiatric events. We aimed to study whether there is risk of incident depression, suicidal ideation or psychosis associated with HCQ as used for RA. METHODS: We performed a new-user cohort study using claims and electronic medical records from 10 sources and 3 countries (Germany, UK and USA). RA patients ≥18 years of age and initiating HCQ were compared with those initiating SSZ (active comparator) and followed up in the short (30 days) and long term (on treatment). Study outcomes included depression, suicide/suicidal ideation and hospitalization for psychosis. Propensity score stratification and calibration using negative control outcomes were used to address confounding. Cox models were fitted to estimate database-specific calibrated hazard ratios (HRs), with estimates pooled where I2 <40%. RESULTS: A total of 918 144 and 290 383 users of HCQ and SSZ, respectively, were included. No consistent risk of psychiatric events was observed with short-term HCQ (compared with SSZ) use, with meta-analytic HRs of 0.96 (95% CI 0.79, 1.16) for depression, 0.94 (95% CI 0.49, 1.77) for suicide/suicidal ideation and 1.03 (95% CI 0.66, 1.60) for psychosis. No consistent long-term risk was seen, with meta-analytic HRs of 0.94 (95% CI 0.71, 1.26) for depression, 0.77 (95% CI 0.56, 1.07) for suicide/suicidal ideation and 0.99 (95% CI 0.72, 1.35) for psychosis. CONCLUSION: HCQ as used to treat RA does not appear to increase the risk of depression, suicide/suicidal ideation or psychosis compared with SSZ. No effects were seen in the short or long term. Use at a higher dose or for different indications needs further investigation. TRIAL REGISTRATION: Registered with EU PAS (reference no. EUPAS34497; http://www.encepp.eu/encepp/viewResource.htm? id=34498). The full study protocol and analysis source code can be found at https://github.com/ohdsi-studies/Covid19EstimationHydroxychloroquine2.

Durability of glycaemic control in patients with type 2 diabetes after metformin failure: Prognostic model derivation and validation using the DISCOVER study.

AIM: To develop and internally validate prognostic models on the long-term durability of glycaemic control in patients with type 2 diabetes after metformin failure. MATERIALS AND METHODS: DISCOVER is a 3-year, prospective observational study across six continents investigating second-line glucose-lowering therapies. In this analysis from 35 countries, we included patients on metformin initiating second-line glucose-lowering medication(s) because of physician-defined lack of efficacy. The outcome was durability of glycaemic control, defined as three consecutive levels of HbA1c at 6-, 12- and 24-month follow-up at target (HbA1c equal to or lower than the level when the physician initiated the second-line therapy in patients with baseline HbA1c ≤7% [53 mmol/mol]; and equal to or lower than 7% in those with baseline HbA1c >7%). We developed and internally validated two prognostic models: a base model, which included age, sex, ethnicity, country income group, baseline HbA1c and second-line therapy, and an advanced model, established through statistical variable selections from a model including base variables and 13 additional predictors selected from a literature review. We used logistic regression to develop and 500 bootstrapping samples to internally validate the models; discrimination and calibration were used to assess model performance. RESULTS: Overall, 896 out of 2995 participants (29.9%) had sustained glycaemic control. The base model performed well: Nagelkerke R2 was 0.13, C-index 0.70 (95% CI: 0.68, 0.71) and bias-corrected C-index 0.69 after internal validation. Diabetes duration, insurance type, estimated glomerular filtration rate and glucose self-monitoring were additionally selected in the advanced model, which had only a slightly better performance compared with the base model: Nagelkerke R2 0.20, C-index 0.71 (95% CI: 0.69, 0.73) and bias-corrected C-index 0.70. Calibration plots showed good calibrations of both validated models. CONCLUSION: These prognostic models, which include simple demographic and routinely collected clinical information, enabled the estimation of the probability of 2-year sustained glycaemic control in patients after metformin failure. The models have been implemented into a web-based tool to support healthcare professionals in their decisions.

Malignancy-related mortality following kidney transplantation is common.

There is a paucity of studies describing malignancy-related mortality after kidney transplantation. To help quantify this, we extracted data for all kidney-alone transplant procedures performed in England between April 2001 and March 2012. Data linkage analysis was performed between Hospital Episode Statistics and the Office for National Statistics to identify all deaths occurring in this cohort. Among 19,103 kidney transplant procedures analyzed (median follow-up 4.4 years), 2085 deaths occurred, of which 376 (18.0%) were due to malignancy (crude mortality rate 361 malignancy-related deaths per 100,000 person-years). Common sites of malignancy-related death were lymphoma (18.4%), followed by lung (17.6%) and renal (9.8%), with 14.1% unspecified. The risk of malignancy-related death increased with age: under 50 (0.8%), 50-59 (2.5%), 60-69 (4.8%), 70-79 (6.5%) and over 80 years (9.1%). Age- and gender-stratified malignancy-related mortality risk difference was higher in the transplant compared with the general population. Cox proportional hazard models identified increased age, pretransplant history of malignancy and deceased-donor kidney transplantation to be independently associated with risk for post-transplant death from malignancy. Thus, malignancy as a cause of post-kidney transplantation death is common and requires heightened surveillance.

Death within the first year after kidney transplantation--an observational cohort study.

The risk of death within the first year postkidney transplantation is not well described in the contemporary era. We extracted data on all kidney transplant procedures performed in England between April 2001 and March 2012. Data linkage analysis was performed between Hospital Episode Statistics and the Office for National Statistics to identify all deaths. Cox proportional hazard models were performed to identify factors associated with 1-year mortality. 566 deaths (3.0%) occurred within the first year post-transplant (from 19,103 kidney transplant procedures analysed). Infection, cardiovascular events and malignancy were classified in 21.6%, 18.3% and 7.4% of death certificates, respectively. Among recipients with prior myocardial infarct history who died within the first year, 38.8% of deaths were attributed to a cardiac-related event. Malignancy-related death was responsible for 61.5% of 1-year mortality for allograft recipients with pretransplant cancer history. 22.1% of deaths included kidney failure as a contributory factor on the death certificate (3.3% specifically stated allograft failure). Variables associated with 1-year mortality included deceased-donor kidney, increasing age, residence in socioeconomically deprived area and history of select medical comorbidities pre-operatively. We conclude 1-year mortality postkidney transplantation is low, but in select allograft recipients, the risk of death increases considerably.

Mortality after pediatric kidney transplantation in England--a population-based cohort study.

The aim of this study was to explore mortality after pediatric kidney transplantation in England over the last decade. We used data from HES to select all kidney transplant procedures performed in England between April 2001 and March 2012. Data linkage analysis was performed with the ONS to identify all deaths occurring among this study cohort. Data for 1189 pediatric recipients were compared to 17 914 adult recipients (number of deaths, 33 vs. 2052, respectively, p < 0.001), with median follow-up 4.4 yr (interquartile range 2.2-7.3 yr). There was no difference in mortality within the pediatric cohort; age 0-1 (n = 25, patient survival 100.0%), age 2-5 (n = 198, patient survival 96.0%), age 6-12 (n = 359, patient survival 97.5%), and age 13-18 (n = 607, patient survival 97.4%), respectively (p = 0.567). The most common causes of death were renal (n = 8, 24.2%), infection (n = 6, 18.2%), and malignancy (n = 5, 15.2%). All deaths from malignancy were secondary to PTLD. In a fully adjusted Cox regression model, only white ethnicity was significantly associated with risk of pediatric mortality post-kidney transplantation (hazard ratio 2.7, 95% confidence interval [1.0-7.3], p = 0.047). To conclude, this population-based cohort study confirms low mortality after pediatric kidney transplantation with short follow-up.

Calibrating Observational Health Record Data Against a Randomized Trial.

Importance: The conditions required for health record data sources to accurately assess treatment effectiveness remain unclear. Emulation of randomized clinical trials (RCTs) with health record data and subsequent calibration of the results can help elucidate this. Objective: To pilot an emulation of the KEYNOTE-189 RCT using a commercially available electronic health record (EHR) data source. Design, Setting, and Participants: This retrospective cohort study used an EHR database spanning from April 2007 to February 2023. Follow-up began on treatment initiation and proceeded until an outcome event, loss to follow-up, end of data, or end of study period (640 days). The population-based cohort was ascertained from EHRs provided by 52 health systems across the US. Eligibility criteria were defined as closely as possible to the benchmark RCT. Patients with non-small cell lung cancer initiating first-line treatment for metastatic disease were included. Patients with evidence of squamous non-small cell lung cancer, primary nonlung malignant neoplasms, or identified EGFR/ALK variations were excluded. Data were analyzed from June to October 2023. Exposures: Initiation of first-line pembrolizumab and chemotherapy and chemotherapy alone. Chemotherapy in both groups was defined as a combination of pemetrexed and platinum-based (carboplatin or cisplatin) therapy. Main Outcomes and Measures: Outcomes of interest were 12-month survival probability and mortality hazard ratio (HR). Results: A total of 1854 patients (mean [SD] age, 63.7 [9.6] years; 971 [52.4%] men) were eligible, including 589 patients who initiated pembrolizumab and chemotherapy and 1265 patients who initiated chemotherapy only. The cohort included 364 Black patients (19.6%) and 1445 White patients (77.9%). The 12-month survival probabilities were 0.60 (95% CI, 0.54-0.65) in the pembrolizumab group and 0.58 (95% CI, 0.55-0.62) in the chemotherapy-only group, compared with 0.69 (95% CI, 0.64-0.74) in the KEYNOTE-189 pembrolizumab group and 0.49 (95% CI, 0.42-0.56) in the KEYNOTE-189 chemotherapy-only group. The mortality HR was 0.95 (95% CI, 0.78-1.16), compared with 0.49 (95% CI, 0.38-0.64) in the KEYNOTE-189 RCT. Conclusions and Relevance: In this cohort study piloting an RCT emulation, results were incongruous with the benchmark trial. Differences in patient treatment and data capture between the RCT and EHR populations, confounding by indication, treatment crossover, and accuracy of captured diagnoses may explain these findings. Future feasibility assessments will require data sources to have important oncology-specific measures curated.

Biomarker-directed targeted therapy plus durvalumab in advanced non-small-cell lung cancer: a phase 2 umbrella trial.

For patients with non-small-cell lung cancer (NSCLC) tumors without currently targetable molecular alterations, standard-of-care treatment is immunotherapy with anti-PD-(L)1 checkpoint inhibitors, alone or with platinum-doublet therapy. However, not all patients derive durable benefit and resistance to immune checkpoint blockade is common. Understanding mechanisms of resistance-which can include defects in DNA damage response and repair pathways, alterations or functional mutations in STK11/LKB1, alterations in antigen-presentation pathways, and immunosuppressive cellular subsets within the tumor microenvironment-and developing effective therapies to overcome them, remains an unmet need. Here the phase 2 umbrella HUDSON study evaluated rational combination regimens for advanced NSCLC following failure of anti-PD-(L)1-containing immunotherapy and platinum-doublet therapy. A total of 268 patients received durvalumab (anti-PD-L1 monoclonal antibody)-ceralasertib (ATR kinase inhibitor), durvalumab-olaparib (PARP inhibitor), durvalumab-danvatirsen (STAT3 antisense oligonucleotide) or durvalumab-oleclumab (anti-CD73 monoclonal antibody). Greatest clinical benefit was observed with durvalumab-ceralasertib; objective response rate (primary outcome) was 13.9% (11/79) versus 2.6% (5/189) with other regimens, pooled, median progression-free survival (secondary outcome) was 5.8 (80% confidence interval 4.6-7.4) versus 2.7 (1.8-2.8) months, and median overall survival (secondary outcome) was 17.4 (14.1-20.3) versus 9.4 (7.5-10.6) months. Benefit with durvalumab-ceralasertib was consistent across known immunotherapy-refractory subgroups. In ATM-altered patients hypothesized to harbor vulnerability to ATR inhibition, objective response rate was 26.1% (6/23) and median progression-free survival/median overall survival were 8.4/22.8 months. Durvalumab-ceralasertib safety/tolerability profile was manageable. Biomarker analyses suggested that anti-PD-L1/ATR inhibition induced immune changes that reinvigorated antitumor immunity. Durvalumab-ceralasertib is under further investigation in immunotherapy-refractory NSCLC.ClinicalTrials.gov identifier: NCT03334617.

Socioeconomic deprivation is independently associated with mortality post kidney transplantation.

The association between area socioeconomic deprivation and mortality post kidney transplantation is unclear. To clarify this, we obtained data from 19,103 kidney transplant procedures performed in England from April 2001 to March 2012. Patient demographics included age, gender, donor type (living or deceased), ethnicity, transplant year, allograft failure, medical comorbidities, and area socioeconomic deprivation (Index of Multiple Deprivation (2010)). Primary and secondary outcome measures were 1- and 5-year mortality with Cox proportional hazard models performed to identify independent factors associated with mortality. Data were broken down into quintiles of patients by area socioeconomic deprivation 1 to 5 (most to least deprived, respectively). At 1 year post transplant, 566 deaths were recorded, with infection being the most common cause of death. Compared with the most deprived individuals (reference point), the least deprived recipients had significantly decreased risk of death at 1 and 5 years post kidney transplant (hazard ratio 0.66, 95% CI (0.57-0.76) and hazard ratio 0.65, 95% CI (0.54-0.77), respectively). Thus, socioeconomic deprivation is independently associated with increased mortality post kidney transplantation.

The Aetion Coalition to Advance Real-World Evidence through Randomized Controlled Trial Emulation Initiative: Oncology.

Legislative and technological advancements over the past decade have given rise to the proliferation of healthcare data generated from routine clinical practice, often referred to as real-world data (RWD). These data have piqued the interest of healthcare stakeholders due to their potential utility in generating evidence to support clinical and regulatory decision making. In the oncology setting, studies leveraging RWD offer distinct advantages that are complementary to randomized controlled trials (RCTs). They also permit the conduct of investigations that may not be possible through prospective designs due to ethics or feasibility. Despite its promise, the use of RWD for the generation of clinical evidence remains controversial due to concerns of unmeasured confounding and other sources of bias that must be carefully addressed in the study design and analysis. To facilitate a better understanding of when RWD can provide reliable conclusions on drug effectiveness, we seek to conduct 10 RWD-based studies that emulate RCTs in oncology using a systematic, protocol-driven approach described herein. Results of this investigation will help inform clinical, scientific, and regulatory stakeholders on the applications of RWD in the context of product labeling expansion, drug safety, and comparative effectiveness in oncology.

The Alignment of Real-World Evidence and Digital Health: Realising the Opportunity.

In the new era of healthcare digitalization, there is a golden opportunity in the overlap between digital health and Real-World Evidence (RWE). In this commentary, we define RWE and digital health and investigate their intersection. We describe the stages in the RWE value chain critical to the evidence generation process, how these stages change with new digital technologies and the opportunities and challenges that arise from how these stages evolve-including their application for stakeholders such as patients, physicians and regulators. We also discuss the current published guidelines and frameworks regarding digital health. We categorise these publications in terms of their clarity as "Extensive", "Intermediate" or "Basic" and according to whether they encompass all levels of digital health or are more focussed in their guidance. Finally, we provide recommendations to increase synergy between RWE and digital health.

Bridging the Gap Between RCTs and RWE Through Endpoint Selection.

This commentary is authored by several industry real-world evidence (RWE) experts, with support from IQVIA, as part of the 'RWE Leadership Forum': a group of Industry Leaders who have come together as non-competitive partners to understand and respond to RWD/E challenges and opportunities with a single expert voice. Here, the forum discusses the value in bridging the industry disconnect between RTCs and RWE, with a view to promoting the use of RWE in the RCT environment. RCT endpoints are explored along several axes including their clinical relevance and their measure of direct patient benefit, and then compared with their real-world counterparts to identify suitable paths, or gaps, for assimilating RWE endpoints into the RCT environment.

Strengthening pharma's contract with society: the value of trusted partnerships between pharma and healthcare facilitated by real-world data.

This White Paper is authored by 11 industry real-world evidence (RWE) experts, with support from IQVIA, as part of the 'RWE Leadership Forum': a group of industry leaders who come together as noncompetitive partners to understand and respond to internal or external RWD/E challenges and opportunities with a single expert voice. Herein we aim to clarify the rules of engagement between pharma and healthcare in order to establish trust-based partnerships, which will unlock unique value for society, including the medical community and the ultimate beneficiary, the patient.

Risk of hydroxychloroquine alone and in combination with azithromycin in the treatment of rheumatoid arthritis: a multinational, retrospective study.

BACKGROUND: Hydroxychloroquine, a drug commonly used in the treatment of rheumatoid arthritis, has received much negative publicity for adverse events associated with its authorisation for emergency use to treat patients with COVID-19 pneumonia. We studied the safety of hydroxychloroquine, alone and in combination with azithromycin, to determine the risk associated with its use in routine care in patients with rheumatoid arthritis. METHODS: In this multinational, retrospective study, new user cohort studies in patients with rheumatoid arthritis aged 18 years or older and initiating hydroxychloroquine were compared with those initiating sulfasalazine and followed up over 30 days, with 16 severe adverse events studied. Self-controlled case series were done to further establish safety in wider populations, and included all users of hydroxychloroquine regardless of rheumatoid arthritis status or indication. Separately, severe adverse events associated with hydroxychloroquine plus azithromycin (compared with hydroxychloroquine plus amoxicillin) were studied. Data comprised 14 sources of claims data or electronic medical records from Germany, Japan, the Netherlands, Spain, the UK, and the USA. Propensity score stratification and calibration using negative control outcomes were used to address confounding. Cox models were fitted to estimate calibrated hazard ratios (HRs) according to drug use. Estimates were pooled where the I 2 value was less than 0·4. FINDINGS: The study included 956 374 users of hydroxychloroquine, 310 350 users of sulfasalazine, 323 122 users of hydroxychloroquine plus azithromycin, and 351 956 users of hydroxychloroquine plus amoxicillin. No excess risk of severe adverse events was identified when 30-day hydroxychloroquine and sulfasalazine use were compared. Self-controlled case series confirmed these findings. However, long-term use of hydroxychloroquine appeared to be associated with increased cardiovascular mortality (calibrated HR 1·65 [95% CI 1·12-2·44]). Addition of azithromycin appeared to be associated with an increased risk of 30-day cardiovascular mortality (calibrated HR 2·19 [95% CI 1·22-3·95]), chest pain or angina (1·15 [1·05-1·26]), and heart failure (1·22 [1·02-1·45]). INTERPRETATION: Hydroxychloroquine treatment appears to have no increased risk in the short term among patients with rheumatoid arthritis, but in the long term it appears to be associated with excess cardiovascular mortality. The addition of azithromycin increases the risk of heart failure and cardiovascular mortality even in the short term. We call for careful consideration of the benefit-risk trade-off when counselling those on hydroxychloroquine treatment. FUNDING: National Institute for Health Research (NIHR) Oxford Biomedical Research Centre, NIHR Senior Research Fellowship programme, US National Institutes of Health, US Department of Veterans Affairs, Janssen Research and Development, IQVIA, Korea Health Industry Development Institute through the Ministry of Health and Welfare Republic of Korea, Versus Arthritis, UK Medical Research Council Doctoral Training Partnership, Foundation Alfonso Martin Escudero, Innovation Fund Denmark, Novo Nordisk Foundation, Singapore Ministry of Health's National Medical Research Council Open Fund Large Collaborative Grant, VINCI, Innovative Medicines Initiative 2 Joint Undertaking, EU's Horizon 2020 research and innovation programme, and European Federation of Pharmaceutical Industries and Associations.

Real world evidence (RWE) - a disruptive innovation or the quiet evolution of medical evidence generation?

Stakeholders in healthcare are increasingly turning to real world evidence (RWE) to inform their decisions, alongside evidence from randomized controlled trials. RWE is generated by analysing data gathered from routine clinical practice, and can be used across the product lifecycle, providing insights into areas including disease epidemiology, treatment effectiveness and safety, and health economic value and impact. Recently, the US Food and Drug Administration and the European Medicines Agency have stated their ambition for greater use of RWE to support applications for new indications, and are now consulting with their stakeholders to formalize standards and expected methods for generating RWE. Pharmaceutical companies are responding to the increasing demands for RWE by developing standards and processes for each stage of the evidence generation pathway. Some conventions are already in place for assuring quality, whereas other processes are specific to the research question and data sources available. As evidence generation increasingly becomes a core role of medical affairs divisions in large pharmaceutical companies, standards of rigour will continue to evolve and improve. Senior pharmaceutical leaders can drive this change by making RWE a core element of their corporate strategy, providing top-level direction on how their respective companies should approach RWE for maximum quality. Here, we describe the current and future areas of RWE application within the pharmaceutical industry, necessary access to data to generate RWE, and the challenges in communicating RWE. Supporting and building on viewpoints from industry and publicly funded research, our perspective is that at each stage of RWE generation, quality will be critical to the impact that RWE has on healthcare decision-makers; not only where RWE is an established and evolving tool, but also in new areas that have the potential to disrupt and to improve drug development pathways.

Can we update the Summary Hospital Mortality Index (SHMI) to make a useful measure of the quality of hospital care? An observational study.

OBJECTIVE: To advance methods for the estimation of hospital performance based upon mortality ratios. DESIGN: Observational study estimating trust performance in a year derived according to comparative standards from a 3-year period, accounting for patient-level case-mix and overdispersion (unexplained variability). PARTICIPANTS: 23 363 630 admissions to the English National Health Service (NHS) by NHS Trust. MAIN OUTCOME MEASURES: Number of SDs (QUality and Outcomes Research Unit Measure, QUORUM banding) and comparative odds of hospital mortality difference from mean performance by trust compared for 2010/2011, 2008/2009 and 2009/2010, accounting for patient-level case-mix. RESULTS: The model was highly predictive of mortality (C statistic=0.93), and well calibrated by risk stratum. There was substantial overdispersion. No trusts were more than 3 SDs above the mean, and only one trust was more than 2 SDs above the mean for 2010/2011. CONCLUSIONS: QUORUM is highly predictive of patient mortality in hospital or up to 30 days after admission. However, like the Summary Hospital Mortality Indicator (SHMI), QUORUM is subjected to considerable remaining legitimate but unexplained variation. It is unlikely that measures like QUORUM and SHMI will be useful beyond identifying a very small number of trusts as potential outliers.