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The objective of this study was to estimate the relative efficacy and safety of targeted therapies for the treatment of metastatic melanoma using a network meta-analysis (NMA).A systematic literature review (SLR) identified studies in Medline, Embase and Cochrane published until November 2020. Screening used prespecified eligibility criteria. Following a transitivity assessment across included studies, Bayesian NMA was conducted.A total of 43 publications reporting 15 targeted therapy trials and 42 reporting 18 immunotherapy trials were retained from the SLR and considered for the NMA. Due to substantial between-study heterogeneity with immunotherapy trials, the analysis considered a network restricted to targeted therapies. Among combination therapies, encorafenib + binimetinib was superior to dabrafenib + trametinib for overall response rate (OR = 1.86; 95 % credible interval [CrI] 1.10, 3.17), superior to vemurafenib + cobimetinib with fewer serious adverse events (SAEs) (OR = 0.51; 95 % CrI 0.29, 0.91) and fewer discontinuations due to AEs (OR = 0.45; 95 % CrI 0.21, 0.96), and superior to atezolizumab + vemurafenib + cobimetinib with fewer SAEs (OR = 0.41; 95 % CrI 0.21, 0.82). Atezolizumab + vemurafenib + cobimetinib and encorafenib + binimetinib were generally comparable for efficacy endpoints. Among double combination therapies, encorafenib + binimetinib showed high probabilities of being better for all efficacy and safety endpoints.This NMA confirms that combination therapies are more efficacious than monotherapies. Encorafenib + binimetinib has a favourable efficacy profile compared to other double combination therapies and a favourable safety profile compared to both double and triple combination therapies.

BackgroundApproximately 20% of patients experience chronic pain after total knee replacement (TKR). The impact of chronic pain after TKR on primary care services in the UK is currently unknown. The aim of this study was to compare primary care consultations and pain medicine prescriptions between patients with and without chronic pain after TKR. MethodsData from 5,055 patients who received TKR between 2009-2016 with anonymised linked data from the Clinical Practice Research Datalink Gold (CPRD) and English Hospital Episode Statistics (HES) Patient Reported Outcome Measures (PROMs) programme were analysed. The exposure time was from 10 years pre-operative to eight years post-operative. Patients with a score ≤14 on the Oxford Knee Score pain component scale at 6 months post-operative were classified as having chronic pain after TKR. Primary care consultations and prescribed pain medicines were quantified, and costs calculated based on national cost data. Results721 patients (14%) had chronic pain after TKR. The prevalence and costs of primary care consultations and pain medicine prescriptions per year were consistently higher for patients with chronic pain after TKR compared with those without chronic pain after TKR; these differences were observed both before and after surgery. There was a substantial and sustained increase in the cost of opioid prescriptions after surgery for patients with chronic pain after TKR, peaking at seven years post-operative. ConclusionsIncreased primary care consultations and pain medicine prescriptions associated with chronic pain after TKR represent a considerable financial cost to primary care services. Evaluation of interventions to reduce the risk of developing this pain condition and improve the early management of pain after TKR are needed to improve outcomes for patients and reduce costs to healthcare services.

Background Although routine NHS data potentially include all patients, confounding limits their use for causal inference. Methods to minimise confounding in observational studies of implantable devices are required to enable the evaluation of patients with severe systemic morbidity who are excluded from many randomised controlled trials. Objectives Stage 1 – replicate the Total or Partial Knee Arthroplasty Trial (TOPKAT), a surgical randomised controlled trial comparing unicompartmental knee replacement with total knee replacement using propensity score and instrumental variable methods. Stage 2 – compare the risk benefits and cost-effectiveness of unicompartmental knee replacement with total knee replacement surgery in patients with severe systemic morbidity who would have been ineligible for TOPKAT using the validated methods from stage 1. Design This was a cohort study. Setting Data were obtained from the National Joint Registry database and linked to hospital inpatient (Hospital Episode Statistics) and patient-reported outcome data. Participants Stage 1 – people undergoing unicompartmental knee replacement surgery or total knee replacement surgery who met the TOPKAT eligibility criteria. Stage 2 – participants with an American Society of Anesthesiologists grade of ≥ 3. Intervention The patients were exposed to either unicompartmental knee replacement surgery or total knee replacement surgery. Main outcome measures The primary outcome measure was the postoperative Oxford Knee Score. The secondary outcome measures were 90-day postoperative complications (venous thromboembolism, myocardial infarction and prosthetic joint infection) and 5-year revision risk and mortality. The main outcome measures for the health economic analysis were health-related quality of life (EuroQol-5 Dimensions) and NHS hospital costs. Results In stage 1, propensity score stratification and inverse probability weighting replicated the results of TOPKAT. Propensity score adjustment, propensity score matching and instrumental variables did not. Stage 2 included 2256 unicompartmental knee replacement patients and 57,682 total knee replacement patients who had severe comorbidities, of whom 145 and 23,344 had linked Oxford Knee Scores, respectively. A statistically significant but clinically irrelevant difference favouring unicompartmental knee replacement was observed, with a mean postoperative Oxford Knee Score difference of Limitations Although some propensity score methods successfully replicated TOPKAT, unresolved confounding may have affected stage 2. Missing Oxford Knee Scores may have led to information bias. Conclusions Propensity score stratification and inverse probability weighting successfully replicated TOPKAT, implying that some (but not all) propensity score methods can be used to evaluate surgical innovations and implantable medical devices using routine NHS data. Unicompartmental knee replacement was safer and more cost-effective than total knee replacement for patients with severe comorbidity and should be considered the first option for suitable patients. Future work Further research is required to understand the performance of propensity score methods for evaluating surgical innovations and implantable devices. Trial registration This trial is registered as EUPAS17435. Funding This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 66. See the NIHR Journals Library website for further project information.

The objective of this cross-sectional study was to assess the relationship between food insecurity and depression in the Mexican population. We used data from the 2012 health and nutrition survey (ENSANUT), which is representative of the Mexican population. Food insecurity was determined by the Latin American and Caribbean Food Security Scale (ELCSA). Depressive symptoms were evaluated using the Center for Epidemiological Studies Depression Scale Short-Form (CES-D-SF). Adjusted logistic regression analyses and ANCOVA were used. Out of 33,011 participants, 5788 (18%) had high depressive symptoms and 24,098 (73%) experienced food insecurity. The adjusted logistic regression analysis showed that, participants with mild food insecurity, (OR = 1.47,95% CI = 1.27 to 1.71), moderate food insecurity (OR = 2.14,95% CI = 1.85 to 2.47) and severe food insecurity (OR = 3.01,95% CI = 2.51 to 3.60,) were more likely to have high depressive symptoms than food secure participants. Participants with moderate food insecurity (OR =1.45, 95% CI = 1.28 to 1.64) and severe food insecurity (OR =2.04, 95% CI = 1.76 to 2.37) were more likely to suffer from depression as compared to participants with mild food insecurity. Participants with severe food insecurity were more likely (OR=1.41, 95% CI = 1.21 to 1.65) to suffer from depression compared to participants with moderate food insecurity. This paper provides an overview of the complex problem of food insecurity and mental health. Despite the unknown causality, the analysis suggests a strong association between depression and food insecurity. This problem calls for much more attention from the scientific community. Given the high prevalence of depression and the high prevalence of household food insecurity in Mexico, the implementation of successful public health programs to improve food security is necessary.

ObjectivesConcern 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.MethodsWe 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

BACKGROUND Major depressive disorder is a chronic condition; its prevalence is expected to grow with the aging trend of high-income countries. Internet-based cognitive-behavioral therapy has proven efficacy in treating major depressive disorder. OBJECTIVE The objective of this study was to assess the cost-effectiveness of implementing a community internet-based cognitive behavioral therapy intervention (Super@, the Spanish program for the MasterMind project) for treating major depressive disorder. METHODS The cost-effectiveness of the Super@ program was assessed with the Monitoring and Assessment Framework for the European Innovation Partnership on Active and Healthy Ageing tool, using a 3-state Markov model. Data from the cost and effectiveness of the intervention were prospectively collected from the implementation of the program by a health care provider in Badalona, Spain; the corresponding data for usual care were gathered from the literature. The health states, transition probabilities, and utilities were computed using Patient Health Questionnaire–9 scores. RESULTS The analysis was performed using data from 229 participants using the Super@ program. Results showed that the intervention was more costly than usual care; the discounted (3%) and nondiscounted incremental cost-effectiveness ratios were €29,367 and €26,484 per quality-adjusted life-year, respectively (approximately US $35,299 and $31,833, respectively). The intervention was cost-effective based on the €30,000 willingness-to-pay threshold typically applied in Spain (equivalent to approximately $36,060). According to the deterministic sensitivity analyses, the potential reduction of costs associated with intervention scale-up would reduce the incremental cost-effectiveness ratio of the intervention, although it remained more costly than usual care. A discount in the incremental effects up to 5% exceeded the willingness-to-pay threshold of €30,000. CONCLUSIONS The Super@ program, an internet-based cognitive behavioral therapy intervention for treating major depressive disorder, cost more than treatment as usual. Nevertheless, its implementation in Spain would be cost-effective from health care and societal perspectives, given the willingness-to-pay threshold of €30,000 compared with treatment as usual.

Background Elective total knee replacement (TKR) is a safe and cost-effective surgical procedure for treating severe knee osteoarthritis (OA). Although complications following surgery are rare, prediction tools could help identify those patients who are at particularly high risk who could then be targeted with preventative interventions. We aimed to develop a simple model to help inform treatment choices. Methods We trained and externally validated adverse event prediction models for patients with TKR using electronic health records (EHR) and claims data from the US (OPTUM, CCAE, MDCR, and MDCD) and general practice data in the UK (IQVIA Medical Research Database ([IMRD], incorporating data from The Health Improvement Network [THIN], a Cegedim database). The target population consisted of patients undergoing a primary TKR, aged ≥40 years and registered in any of the contributing data sources for ≥1 year before surgery. LASSO logistic regression models were developed for four adverse outcomes: post-operative (90-day) mortality, venous thromboembolism (VTE), readmission, and long-term (5-year) revision surgery. A second model was developed with a reduced feature set to increase interpretability and usability. Findings A total of 508,082 patients were included, with sample size per data source ranging from 1,853 to 158,549 patients. Overall, 90-day mortality, VTE, and readmission prevalence occurred in a range of 0.20%-0.32%, 1.7%-3.0% and 2.2%-4.8%, respectively. Five-year revision surgery was observed in 1.5%-3.1% of patients. The full model predicting 90-day mortality yielded AUROC of 0.78 when trained in OPTUM and yielded an AUROC of 0.70 when externally validated on THIN. We then developed a 12 variable model which achieved internal AUROC of 0.77 and external AUROC of 0.71 in THIN. The discriminative performances of the models predicting 90-day VTE, readmission, and 5-year revision were consistently poor across the datasets (AUROC Interpretation We developed and externally validated a simple prediction model based on sex, age, and 10 comorbidities that can identify patients at high risk of short-term mortality following TKR. Our model had a greater discriminative ability than the Charlson Comorbidity Index in predicting 90-day mortality. The 12-feature mortality model is easily implemented and the performance suggests it could be used to inform evidence based shared decision-making prior to surgery and for appropriate precautions to be taken for those at high risk. The other outcomes examined had low performance. Funding This activity under the European Health Data & Evidence Network (EHDEN) has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 806968. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA. The sponsor of the study did not have any involvement in the writing of the manuscript or the decision to submit it for publication. The research was supported by the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC). DPA is funded by a National Institute for Health Research Clinician Scientist award (CS-2013-13-012). TDS is funded by the Department of Health of the Generalitat de Catalunya under the Strategic Plan for Research and Innovation in Health (PERIS; SLT002/16/00308). The views expressed in this publication are those of the authors and not those of the NHS, the National Institute for Health Research or the Department of Health. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication. Key Points Question Is it possible to predict adverse events following total knee replacement? Findings Mortality was the only adverse event studied that we were able to predict with adequate performance. We produced a 12 variable prediction model for 90-day post-operative mortality that achieved an AUROC of 0.77 on internal test validation (Optum) and 0.71 when externally validated in THIN. The model also showed adequate calibration. Meaning Patients can now be presented with an accurate risk assessment for short term mortality such that they are well-informed before the decision for surgery is taken. Importance Total Knee Replacement is generally a safe, effective procedure that is performed on thousands of patients each year. However, a small number of those patients will experience adverse events. Due to the surgery’s elective nature, a well calibrated, high performing risk model could pre-emptively inform the patient and clinician decision making process and help to guide preventative treatment.

Author(s): Lane, Jennifer CE; Weaver, James; Kostka, Kristin; Duarte-Salles, Talita; Abrahao, Maria Tereza F; Alghoul, Heba; Alser, Osaid; Alshammari, Thamir M; Areia, Carlos; Biedermann, Patricia; Banda, Juan M; Burn, Edward; Casajust, Paula; Fister, Kristina; Hardin, Jill; Hester, Laura; Hripcsak, George; Kaas-Hansen, Benjamin Skov; Khosla, Sajan; Kolovos, Spyros; Lynch, Kristine E; Makadia, Rupa; Mehta, Paras P; Morales, Daniel R; Morgan-Stewart, Henry; Mosseveld, Mees; Newby, Danielle; Nyberg, Fredrik; Ostropolets, Anna; Woong Park, Rae; Prats-Uribe, Albert; Rao, Gowtham A; Reich, Christian; Rijnbeek, Peter; Sena, Anthony G; Shoaibi, Azza; Spotnitz, Matthew; Subbian, Vignesh; Suchard, Marc A; Vizcaya, David; Wen, Haini; Wilde, Marcel de; Xie, Junqing; You, Seng Chan; Zhang, Lin; Lovestone, Simon; Ryan, Patrick; Prieto-Alhambra, Daniel; OHDSI-COVID-19 consortium | Abstract: ObjectivesConcern 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.MethodsWe 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 l40%.ResultsA 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.ConclusionHCQ 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 registrationRegistered 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.

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 I² 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. Selfcontrolled 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.

ObjectivesConcern has been raised in the rheumatological community regarding recent regulatory warnings that hydroxychloroquine used in the COVID-19 pandemic could cause acute psychiatric events. We aimed to study whether there is risk of incident depression, suicidal ideation, or psychosis associated with hydroxychloroquine as used for rheumatoid arthritis (RA).MethodsNew user cohort study using claims and electronic medical records from 10 sources and 3 countries (Germany, UK and US). RA patients aged 18+ and initiating hydroxychloroquine were compared to those initiating sulfasalazine (active comparator) and followed up in the short (30-day) 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 (HR), with estimates pooled where I2Results918,144 and 290,383 users of hydroxychloroquine and sulfasalazine, respectively, were included. No consistent risk of psychiatric events was observed with short-term hydroxychloroquine (compared to sulfasalazine) use, with meta-analytic HRs of 0.96 [0.79-1.16] for depression, 0.94 [0.49-1.77] for suicide/suicidal ideation, and 1.03 [0.66-1.60] for psychosis. No consistent long-term risk was seen, with meta-analytic HRs 0.94 [0.71-1.26] for depression, 0.77 [0.56-1.07] for suicide/suicidal ideation, and 0.99 [0.72-1.35] for psychosis.ConclusionsHydroxychloroquine as used to treat RA does not appear to increase the risk of depression, suicide/suicidal ideation, or psychosis compared to sulfasalazine. No effects were seen in the short or long term. Use at higher dose or for different indications needs further investigation.TRIAL REGISTRATIONRegistered with EU PAS; Reference number 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/Covid19EstimationHydroxychloroquine.WHAT IS ALREADY KNOWN ON THIS TOPICRecent regulatory warnings have raised concerns of potential psychiatric side effects of hydroxychloroquine at the doses used to treat COVID-19, generating concern in the rheumatological communitySerious psychiatric adverse events such as suicide, acute psychosis, and depressive episodes have been identified by the US Food and Drug Administration (FDA) adverse events reporting system and at case report levelWHAT THIS STUDY ADDSThis is the largest study on the neuro-psychiatric safety of hydroxychloroquine to date, including >900,000 users treated for their RA in country-level or private health care systems in Germany, the UK, and the USWe find no association between the use of hydroxychloroquine and the risk of depression, suicide/suicidal ideation, or severe psychosis compared to sulfasalazineHOW MIGHT THIS IMPACT ON CLINICAL PRACTICEOur data shows no association between hydroxychloroquine treatment for RA and risk of depression, suicide or psychosis compared to sulfasalazine. These findings do not support stopping or switching hydroxychloroquine treatment as used for RA due to recent concerns based on COVID-19 treated patients.

Summary Hospital use by patients with osteogenesis imperfecta was largely unknown. This study found that the English NHS provides a significant number of hospital admissions to these patients, translating into large costs to the NHS. Admissions and costs both increased over time. Children under 14 years old accounted for more of the admissions and costs than any other age group. Introduction The aim of this study was to characterise hospital use by patients with osteogenesis imperfecta (OI) in the English National Health Service (NHS). Methods Routinely collected aggregate data about all inpatient hospital records from patients with OI were used for the period 1 April 2014 to 31 March 2018. Information was extracted on number of admissions, number of patients, length of stay, and costs. Hospital use was summarised using descriptive statistics, categorising patients into 5-year age groups. Results There were 16,245 hospital admissions for OI patients during the analysis period, with a total cost to the NHS of £24,052,451. Of the 4370 patients involved, 2700 (62%) were female. Female patients averaged 3.3 admissions per year and male patients 4.4 admissions per year. Patients aged 0 to 14 years old accounted for 54% of all admissions. Those aged 90 to 94 years had the longest average length of stay per admission (10.5 days) of any age group. Elective admissions cost on average £1260 and non-elective admissions £2529. Over the 4-year study period, number of admissions increased on average by 2.1% per year and number of patients by 6.4% per year. Conclusion The treatment of patients with OI is associated with a significant number of hospital admissions at an important cost for the NHS, with both number of admissions and costs increasing over time. Children below the age of 14 years had more admissions at a greater total cost than other ages, while the oldest adults had longer average stays and higher costs per admission.

Comorbid conditions appear to be common among individuals hospitalised with coronavirus disease 2019 (COVID-19) but estimates of prevalence vary and little is known about the prior medication use of patients. Here, we describe the characteristics of adults hospitalised with COVID-19 and compare them with influenza patients. We include 34,128 (US: 8362, South Korea: 7341, Spain: 18,425) COVID-19 patients, summarising between 4811 and 11,643 unique aggregate characteristics. COVID-19 patients have been majority male in the US and Spain, but predominantly female in South Korea. Age profiles vary across data sources. Compared to 84,585 individuals hospitalised with influenza in 2014-19, COVID-19 patients have more typically been male, younger, and with fewer comorbidities and lower medication use. While protecting groups vulnerable to influenza is likely a useful starting point in the response to COVID-19, strategies will likely need to be broadened to reflect the particular characteristics of individuals being hospitalised with COVID-19., Detailed knowledge of the characteristics of COVID-19 patients helps with public health planning. Here, the authors use routinely-collected data from seven databases in three countries to describe the characteristics of >30,000 patients admitted with COVID-19 and compare them with those admitted for influenza in previous years.

ObjectivesTo estimate COVID-19 infections and deaths in healthcare workers (HCWs) from a global perspective.DesignScoping review.MethodsTwo parallel searches of academic bibliographic databases and grey literature were undertaken. Governments were also contacted for further information where possible. Due to the time-sensitive nature of the review and the need to report the most up-to-date information for an ever-evolving situation, there were no restrictions on language, information sources utilised, publication status, and types of sources of evidence. The AACODS checklist was used to appraise each source of evidence.Outcome measuresPublication characteristics, country-specific data points, COVID-19 specific data, demographics of affected HCWs, and public health measures employedResultsA total of 152,888 infections and 1413 deaths were reported. Infections were mainly in women (71.6%) and nurses (38.6%), but deaths were mainly in men (70.8%) and doctors (51.4%). Limited data suggested that general practitioners and mental health nurses were the highest risk specialities for deaths. There were 37.17 deaths reported per 100 infections for healthcare workers aged over 70. Europe had the highest absolute numbers of reported infections (119628) and deaths (712), but the Eastern Mediterranean region had the highest number of reported deaths per 100 infections (5.7).ConclusionsHCW COVID-19 infections and deaths follow that of the general world population. The reasons for gender and speciality differences require further exploration, as do the low rates reported from Africa and India. Although physicians working in certain specialities may be considered high-risk due to exposure to oronasal secretions, the risk to other specialities must not be underestimated. Elderly HCWs may require assigning to less risky settings such as telemedicine, or administrative positions. Our pragmatic approach provides general trends, and highlights the need for universal guidelines for testing and reporting of infections in HCWs.Summary BoxWhat is already known on this topicIn China, studies documented over 3,300 confirmed cases of infected healthcare workers in early March. In the United States, as high as 19% of patients had been identified as healthcare workers. There are no studies that perform a global examination of COVID-19 infections and deaths in the health workforce.What this study addsTo our knowledge, this is the first study assessing the number of healthcare workers who have been infected with or died from COVID-19 globally. The data from our study suggest that although infections were mainly in women and nurses, COVID-19 related deaths were mainly in men and doctors; in addition, our study found that Europe had the highest numbers of infection and death, but the lowest case-fatality-rate, while the Eastern Mediterranean had the highest case-fatality-rate.

BackgroundHydroxychloroquine has recently received Emergency Use Authorization by the FDA and is currently prescribed in combination with azithromycin for COVID-19 pneumonia. We studied the safety of hydroxychloroquine, alone and in combination with azithromycin.MethodsNew user cohort studies were conducted including 16 severe adverse events (SAEs). Rheumatoid arthritis patients aged 18+ and initiating hydroxychloroquine were compared to those initiating sulfasalazine and followed up over 30 days. Self-controlled case series (SCCS) were conducted to further establish safety in wider populations. Separately, SAEs associated with hydroxychloroquine- azithromycin (compared to hydroxychloroquine-amoxicillin) were studied. Data comprised 14 sources of claims data or electronic medical records from Germany, Japan, Netherlands, Spain, UK, and USA. Propensity score stratification and calibration using negative control outcomes were used to address confounding. Cox models were fitted to estimate calibrated hazard ratios (CalHRs) according to drug use. Estimates were pooled where I2ResultsOverall, 956,374 and 310,350 users of hydroxychloroquine and sulfasalazine, and 323,122 and 351,956 users of hydroxychloroquine-azithromycin and hydroxychloroquine-amoxicillin were included. No excess risk of SAEs was identified when 30-day hydroxychloroquine and sulfasalazine use were compared. SCCS confirmed these findings. However, when azithromycin was added to hydroxychloroquine, we observed an increased risk of 30-day cardiovascular mortality (CalHR2.19 [1.22- 3.94]), chest pain/angina (CalHR 1.15 [95% CI 1.05-1.26]), and heart failure (CalHR 1.22 [95% CI 1.02- 1.45])ConclusionsShort-term hydroxychloroquine treatment is safe, but addition of azithromycin may induce heart failure and cardiovascular mortality, potentially due to synergistic effects on QT length. We call for caution if such combination is to be used in the management of Covid-19.Trial registration numberRegistered with EU PAS; Reference number 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/Covid19EstimationHydroxychloroquine.Funding sourcesThis research received partial support from the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC) and Senior Research Fellowship (DPA), US National Institutes of Health, Janssen Research & Development, IQVIA, and by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea [grant number: HI16C0992]. Personal funding included Versus Arthritis [21605] (JL), MRC-DTP [MR/K501256/1] (JL), MRC and FAME (APU). The European Health Data & Evidence Network has received funding from the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No 806968. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA. No funders had a direct role in this study. The views and opinions expressed are those of the authors and do not necessarily reflect those of the Clinician Scientist Award programme, NIHR, NHS or the Department of Health, England.

Objectives Depression is associated with considerable impairments in health-related quality-of-life. However, the relationship between different health states related to depression severity and utility scores is unclear. The aim of this study was to evaluate whether utility scores are different for various health states related to depression severity. Methods We gathered individual participant data from ten randomized controlled trials evaluating depression treatments. The UK EQ-5D and SF-6D tariffs were used to generate utility scores. We defined five health states that were proposed from American Psychiatric Association and National Institute for Clinical Excellence guidelines: remission, minor depression, mild depression, moderate depression, and severe depression. We performed multilevel linear regression analysis. Results We included 1629 participants in the analyses. The average EQ-5D utility scores for the five health states were 0.70 (95% CI 0.67–0.73) for remission, 0.62 (95% CI 0.58–0.65) for minor depression, 0.57 (95% CI 0.54–0.61) for mild depression, 0.52 (95%CI 0.49–0.56) for moderate depression, and 0.39 (95% CI 0.35–0.43) for severe depression. In comparison with the EQ-5D, the utility scores based on the SF-6D were similar for remission (EQ-5D = 0.70 vs. SF-6D = 0.69), but higher for severe depression (EQ-5D = 0.39 vs. SF-6D = 0.55). Conclusions We observed statistically significant differences in utility scores between depression health states. Individuals with less severe depressive symptoms had on average statistically significant higher utility scores than individuals suffering from more severe depressive symptomatology. In the present study, EQ-5D had a larger range of values as compared to SF-6D. Electronic supplementary material The online version of this article (doi: 10.1007/s11136-017-1536-2) contains supplementary material, which is available to authorized users.

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 I2 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.

Background There is uncertainty around whether to use unicompartmental knee replacement (UKR) or total knee replacement (TKR) for individuals with osteoarthritis confined to a single compartment of the knee. We aimed to emulate the design of the Total or Partial Knee Arthroplasty Trial (TOPKAT) using routinely collected data to assess whether the efficacy results reported in the trial translate into effectiveness in routine practice, and to assess comparative safety. Methods We did a population-based network study using data from four US and one UK health-care database, part of the Observational Health Data Sciences and Informatics network. The inclusion criteria were the same as those for TOPKAT; briefly, we identified patients aged at least 40 years with osteoarthritis who had undergone UKR or TKR and who had available data for at least one year prior to surgery. Patients were excluded if they had evidence of previous knee arthroplasty, knee fracture, knee surgery (except diagnostic), rheumatoid arthritis, infammatory arthropathies, or septic arthritis. Opioid use from 91–365 days after surgery, as a proxy for persistent pain, was assessed for all participants in all databases. Postoperative complications (ie, venous thromboembolism, infection, readmission, and mortality) were assessed over the 60 days after surgery and implant survival (as measured by revision procedures) was assessed over the 5 years after surgery. Outcomes were assessed in all databases, except for readmission, which was assessed in three of the databases, and mortality, which was assessed in two of the databases. Propensity score matched Cox proportional hazards models were fitted for each outcome. Calibrated hazard ratios (cHRs) were generated for each database to account for observed differences in control outcomes, and cHRs were then combined using meta-analysis. Findings 33 867 individuals who received UKR and 557 831 individuals who received TKR between Jan 1, 2005, and April 30, 2018, were eligible for matching. 32 379 with UKR and 250 377 with TKR were propensity score matched and informed the analyses. UKR was associated with a reduced risk of postoperative opioid use (cHR from meta-analysis 0·81, 95% CI 0·73–0·90) and a reduced risk of venous thromboembolism (0·62, 0·36–0·95), whereas no difference was seen for infection (0·85, 0·51–1·37) and readmission (0·79, 0·47–1·25). Evidence was insufficient to conclude whether there was a reduction in risk of mortality. UKR was also associated with an increased risk of revision (1·64, 1·40–1·94). Interpretation UKR was associated with a reduced risk of postoperative opioid use compared with TKR, which might indicate a reduced risk of persistent pain after surgery. UKR was associated with a lower risk of venous thromboembolism but an increased risk of revision compared with TKR. These findings can help to inform shared decision making for individuals eligible for knee replacement surgery.

Purpose Approximately 70% of adults in Mexico are overweight or obese. Unhealthy lifestyle behaviors are also prevalent. We examined the association of three lifestyle behaviors with body mass index (BMI) categories in adults from Mexico. Methods We used publicly available data from the ENSANUT 2016 survey (n = 6419). BMI was used to categorize participants. Differences in sleep duration, suffering from symptoms of insomnia, TV watching time, time in front of any screen, vigorous physical activity (yes vs no), moderate physical activity (> 30 min/day—yes vs. no) and walking (> 60 min/day—yes vs. no) were compared across BMI groups using adjusted linear and logistic regression analyses. Results Thirty-nine percent of participants were overweight and 37% obese. Time in front of TV, in front of any screen, sleep duration and physical activity were significantly associated with overweight and obesity. Compared to normal weight participants, participants in the obese II category spend on average 0.60 h/day (95% CI 0.36–0.84, p = 0.001) and participants in the obese III category 0.54 h/day (95% CI 0.19–0.89, p p p ≤ 0.003), or walking (OR = 0.65, 95% CI 0.49–0.88, p = 0.005). Conclusion Screen time, sleeping hours, and physical activity were associated with overweight and obesity. However, these associations were not consistent across all BMI categories. Assuming established causal connections, overweight individuals and individuals with obesity would benefit from reduced screen time and engaging in moderate/vigorous physical activity. Level of evidence Level III: observational case-control analytic study.

Background Multiple myeloma (MM) is associated with high healthcare resource utilisation and increasing hospitalisation rates. The aim of this study was to characterise the hospital use by patients with MM in the English National Health Service (NHS). Methods Routinely-collected aggregate data about all NHS-funded hospital admissions of patients with MM were analysed. Data were obtained from the English Hospital Episodes Statistics on admissions between 1 April 2014 and 31 March 2018. Results A total of 754,345 admissions were reported over four years, equivalent to a mean of 188,586 admissions per year. Of the 41,845 patients admitted during this period, 42% were women and 58% men. From the total admissions, 90% were elective and 10% unplanned. Mean annual estimated costs over the period were £46 million for elective and £56 million for unplanned admissions. The number of elective admissions increased by 4.5% with costs increasing 1.5% per year; for unplanned admissions, these figures were 4.1% and 9.0%, respectively. Conclusions MM is associated with a significant number of hospital admissions and NHS costs. The majority of the hospital admissions are elective, but the highest burden in terms of costs relates to unplanned admissions, with numbers increasing over time.

Background Major depressive disorder is a chronic condition; its prevalence is expected to grow with the aging trend of high-income countries. Internet-based cognitive-behavioral therapy has proven efficacy in treating major depressive disorder. Objective The objective of this study was to assess the cost-effectiveness of implementing a community internet-based cognitive behavioral therapy intervention (Super@, the Spanish program for the MasterMind project) for treating major depressive disorder. Methods The cost-effectiveness of the Super@ program was assessed with the Monitoring and Assessment Framework for the European Innovation Partnership on Active and Healthy Ageing tool, using a 3-state Markov model. Data from the cost and effectiveness of the intervention were prospectively collected from the implementation of the program by a health care provider in Badalona, Spain; the corresponding data for usual care were gathered from the literature. The health states, transition probabilities, and utilities were computed using Patient Health Questionnaire–9 scores. Results The analysis was performed using data from 229 participants using the Super@ program. Results showed that the intervention was more costly than usual care; the discounted (3%) and nondiscounted incremental cost-effectiveness ratios were €29,367 and €26,484 per quality-adjusted life-year, respectively (approximately US $35,299 and $31,833, respectively). The intervention was cost-effective based on the €30,000 willingness-to-pay threshold typically applied in Spain (equivalent to approximately $36,060). According to the deterministic sensitivity analyses, the potential reduction of costs associated with intervention scale-up would reduce the incremental cost-effectiveness ratio of the intervention, although it remained more costly than usual care. A discount in the incremental effects up to 5% exceeded the willingness-to-pay threshold of €30,000. Conclusions The Super@ program, an internet-based cognitive behavioral therapy intervention for treating major depressive disorder, cost more than treatment as usual. Nevertheless, its implementation in Spain would be cost-effective from health care and societal perspectives, given the willingness-to-pay threshold of €30,000 compared with treatment as usual.

Background An increasing number of model-based studies that evaluate the cost effectiveness of treatments for depression are being published. These studies have different characteristics and use different simulation methods. Objective We aimed to systematically review model-based studies evaluating the cost effectiveness of treatments for depression and examine which modelling technique is most appropriate for simulating the natural course of depression. Methods The literature search was conducted in the databases PubMed, EMBASE and PsycInfo between 1 January 2002 and 1 October 2016. Studies were eligible if they used a health economic model with quality-adjusted life-years or disability-adjusted life-years as an outcome measure. Data related to various methodological characteristics were extracted from the included studies. The available modelling techniques were evaluated based on 11 predefined criteria. Results This methodological review included 41 model-based studies, of which 21 used decision trees (DTs), 15 used cohort-based state-transition Markov models (CMMs), two used individual-based state-transition models (ISMs), and three used discrete-event simulation (DES) models. Just over half of the studies (54%) evaluated antidepressants compared with a control condition. The data sources, time horizons, cycle lengths, perspectives adopted and number of health states/events all varied widely between the included studies. DTs scored positively in four of the 11 criteria, CMMs in five, ISMs in six, and DES models in seven. Conclusion There were substantial methodological differences between the studies. Since the individual history of each patient is important for the prognosis of depression, DES and ISM simulation methods may be more appropriate than the others for a pragmatic representation of the course of depression. However, direct comparisons between the available modelling techniques are necessary to yield firm conclusions. Electronic supplementary material The online version of this article (doi:10.1007/s41669-017-0014-7) contains supplementary material, which is available to authorized users.

BackgroundSeveral meta-analyses have shown that psychotherapy is effective for reducing depressive symptom severity. However, the impact on quality of life (QoL) is as yet unknown.AimsTo investigate the effectiveness of psychotherapy for depression on global QoL and on the mental health and physical health components of QoL.MethodWe conducted a meta-analysis of 44 randomised clinical trials comparing psychotherapy for adults experiencing clinical depression or elevated depressive symptoms with a control group. We used subgroup analyses to explore the influence of various study characteristics on the effectiveness of treatment.ResultsWe detected a small to moderate effect size (Hedges'g= 0.33, 95% CI 0.24–0.42) for global QoL, a moderate effect size for the mental health component (g= 0.42, 95% CI 0.33–0.51) and, after removing an outlier, a small but statistically significant effect size for the physical health component (g= 0.16, 95% CI 0.05–0.27). Multivariate meta-regression analyses showed that the effect size of depressive symptoms was significantly related to the effect size of the mental health component of QoL. The effect size of depressive symptoms was not related to global QoL or the physical health component.ConclusionsPsychotherapy for depression has a positive impact on the QoL of patients with depression. Improvements in QoL are not fully explained by improvements in depressive symptom severity.

Purpose Obesity and depression are among the leading causes of disability in Mexico, but their association has not been explored yet. The aim of the current study was to investigate the association between obesity and depression in Mexican population. Methods We used data from the health and nutrition survey (ENSANUT 2012), which is representative of the Mexican population. Obesity was determined using the body mass index (BMI) and abdominal obesity by measuring waist circumference. Depressive symptoms were reported using the Center for Epidemiological Studies Depression Scale Short-Form (CES-D-SF, scale 0–21). Regression analyses were performed between obesity and depression, adjusting for gender, age, living with a partner, education, and diabetes history. Results Obese women had 1.28 (95% CI 1.07–1.53) times the odds of having depression in comparison with normal-weight women, whereas no association was found for men (OR 0.94; 95% CI 0.74–1.19). A significant association between BMI and depressive symptoms score (β = 0.05, 95% CI 0.02–0.07) was present in women, but no association was found for men (β = − 0.02, 95% CI − 0.05 to 0.00). There was a statistically significant association between waist circumference and depression scores again for women (β = 0.03, 95% CI 0.01–0.04) but not for men (β = 0.00, 95% CI − 0.01 to 0.01). No associations were found between abdominal obesity and depression for both genders. No association was found between different obesity severity levels and depression for both genders. Conclusion Obesity was associated with depression in Mexican women, whereas no association was found between obesity and depression in men.

Background: Different treatment alternatives exist for psychological disorders. Both clinical and cost effectiveness of treatment are crucial aspects for policy makers, therapists, and patients and thus play major roles for healthcare decision-making. At the start of an intervention, it is often not clear which specific individuals benefit most from a particular intervention alternative or how costs will be distributed on an individual patient level.Objective: This study aimed at predicting the individual outcome and costs for patients before the start of an internet-based intervention. Based on these predictions, individualized treatment recommendations can be provided. Thus, we expand the discussion of personalized treatment recommendation.Methods: Outcomes and costs were predicted based on baseline data of 350 patients from a two-arm randomized controlled trial that compared treatment as usual and blended therapy for depressive disorders. For this purpose, we evaluated various machine learning techniques, compared the predictive accuracy of these techniques, and revealed features that contributed most to the prediction performance. We then combined these predictions and utilized an incremental cost-effectiveness ratio in order to derive individual treatment recommendations before the start of treatment.Results: Predicting clinical outcomes and costs is a challenging task that comes with high uncertainty when only utilizing baseline information. However, we were able to generate predictions that were more accurate than a predefined reference measure in the shape of mean outcome and cost values. Questionnaires that include anxiety or depression items and questions regarding the mobility of individuals and their energy levels contributed to the prediction performance. We then described how patients can be individually allocated to the most appropriate treatment type. For an incremental cost-effectiveness threshold of 25,000 €/quality-adjusted life year, we demonstrated that our recommendations would have led to slightly worse outcomes (1.98%), but with decreased cost (5.42%).Conclusions: Our results indicate that it was feasible to provide personalized treatment recommendations at baseline and thus allocate patients to the most beneficial treatment type. This could potentially lead to improved decision-making, better outcomes for individuals, and reduced health care costs. Background: Different treatment alternatives exist for psychological disorders. Both clinical and cost effectiveness of treatment are crucial aspects for policy makers, therapists, and patients and thus play major roles for healthcare decision-making. At the start of an intervention, it is often not clear which specific individuals benefit most from a particular intervention alternative or how costs will be distributed on an individual patient level.Objective: This study aimed at predicting the individual outcome and costs for patients before the start of an internet-based intervention. Based on these predictions, individualized treatment recommendations can be provided. Thus, we expand the discussion of personalized treatment recommendation.Methods: Outcomes and costs were predicted based on baseline data of 350 patients from a two-arm randomized controlled trial that compared treatment as usual and blended therapy for depressive disorders. For this purpose, we evaluated various machine learning techniques, compared the predictive accuracy of these techniques, and revealed features that contributed most to the prediction performance. We then combined these predictions and utilized an incremental cost-effectiveness ratio in order to derive individual treatment recommendations before the start of treatment.Results: Predicting clinical outcomes and costs is a challenging task that comes with high uncertainty when only utilizing baseline information. However, we were able to generate predictions that were more accurate than a predefined reference measure in the shape of mean outcome and cost values. Questionnaires that include anxiety or depression items and questions regarding the mobility of individuals and their energy levels contributed to the prediction performance. We then described how patients can be individually allocated to the most appropriate treatment type. For an incremental cost-effectiveness threshold of 25,000 €/quality-adjusted life year, we demonstrated that our recommendations would have led to slightly worse outcomes (1.98%), but with decreased cost (5.42%).Conclusions: Our results indicate that it was feasible to provide personalized treatment recommendations at baseline and thus allocate patients to the most beneficial treatment type. This could potentially lead to improved decision-making, better outcomes for individuals, and reduced health care costs.

BACKGROUND Different treatment alternatives exist for psychological disorders. Both clinical and cost effectiveness of treatment are crucial aspects for policy makers, therapists, and patients and thus play major roles for healthcare decision-making. At the start of an intervention, it is often not clear which specific individuals benefit most from a particular intervention alternative or how costs will be distributed on an individual patient level. OBJECTIVE This study aimed at predicting the individual outcome and costs for patients before the start of an internet-based intervention. Based on these predictions, individualized treatment recommendations can be provided. Thus, we expand the discussion of personalized treatment recommendation. METHODS Outcomes and costs were predicted based on baseline data of 350 patients from a two-arm randomized controlled trial that compared treatment as usual and blended therapy for depressive disorders. For this purpose, we evaluated various machine learning techniques, compared the predictive accuracy of these techniques, and revealed features that contributed most to the prediction performance. We then combined these predictions and utilized an incremental cost-effectiveness ratio in order to derive individual treatment recommendations before the start of treatment. RESULTS Predicting clinical outcomes and costs is a challenging task that comes with high uncertainty when only utilizing baseline information. However, we were able to generate predictions that were more accurate than a predefined reference measure in the shape of mean outcome and cost values. Questionnaires that include anxiety or depression items and questions regarding the mobility of individuals and their energy levels contributed to the prediction performance. We then described how patients can be individually allocated to the most appropriate treatment type. For an incremental cost-effectiveness threshold of 25,000 €/quality-adjusted life year, we demonstrated that our recommendations would have led to slightly worse outcomes (1.98%), but with decreased cost (5.42%). CONCLUSIONS Our results indicate that it was feasible to provide personalized treatment recommendations at baseline and thus allocate patients to the most beneficial treatment type. This could potentially lead to improved decision-making, better outcomes for individuals, and reduced health care costs.

BACKGROUND: There is limited evidence on the cost effectiveness of Internet-based treatments for depression. The aim was to evaluate the cost effectiveness of guided Internet-based interventions for depression compared to controls.METHODS: Individual-participant data from five randomized controlled trials (RCT), including 1,426 participants, were combined. Cost-effectiveness analyses were conducted at 8 weeks, 6 months, and 12 months follow-up.RESULTS: The guided Internet-based interventions were more costly than the controls, but not statistically significant (12 months mean difference = €406, 95% CI: - 611 to 1,444). The mean differences in clinical effects were not statistically significant (12 months mean difference = 1.75, 95% CI: - .09 to 3.60 in Center for Epidemiologic Studies Depression Scale [CES-D] score, .06, 95% CI: - .02 to .13 in response rate, and .00, 95% CI: - .03 to .03 in quality-adjusted life-years [QALYs]). Cost-effectiveness acceptability curves indicated that high investments are needed to reach an acceptable probability that the intervention is cost effective compared to control for CES-D and response to treatment (e.g., at 12-month follow-up the probability of being cost effective was .95 at a ceiling ratio of 2,000 €/point of improvement in CES-D score). For QALYs, the intervention's probability of being cost effective compared to control was low at the commonly accepted willingness-to-pay threshold (e.g., at 12-month follow-up the probability was .29 and. 31 at a ceiling ratio of 24,000 and 35,000 €/QALY, respectively).CONCLUSIONS: Based on the present findings, guided Internet-based interventions for depression are not considered cost effective compared to controls. However, only a minority of RCTs investigating the clinical effectiveness of guided Internet-based interventions also assessed cost effectiveness and were included in this individual-participant data meta-analysis.

BACKGROUND: Health-economic models are used to evaluate the long-term cost-effectiveness of an intervention and typically include treatment as usual (TAU) as comparator. Part of the data used for these models are acquired from the literature and thus valid information is needed on the effects of TAU on depression. The aim of the current meta-analysis was to examine positive and negative outcomes of major depression for patients receiving TAU.METHODS: We conducted a systematic literature search in PubMed, EMBASE, PsycInfo, and the Cochrane Central Register of Controlled Trials. Eligible studies were randomized controlled trials including a TAU group for depression. The quality of the included studies was assessed using the criteria described in the "Risk of bias assessment tool". Four separate meta-analyses were performed to estimate remission, response, reliable change and deterioration rates at short-term (≤6 months from baseline).RESULTS: Thirty-eight studies including 2099 patients in the TAU were identified. Nine studies (24%) met five or six quality criteria, 17 studies (44%) met three or four quality criteria and 12 studies (32%) met one or two quality criteria. After adjusting for publication bias, the first meta-analysis (n=33) showed that 33% of the patients remitted from depression. The second meta-analysis (n=13) demonstrated that 27% of the patients responded to treatment, meaning that their depressive symptom decreased at least 50% from baseline to follow-up measurement. The third meta-analysis (n=7) indicated that 31% of the patients showed a reliable change, meaning that their depressive symptoms improved more than expected by random variation alone. Finally, 12% of the patients deteriorated, meaning that their depressive symptoms became more severe.LIMITATIONS: Statistical heterogeneity was substantial in most analyses and was not fully explained by subgroup analyses. The quality of the included studies was moderate. This may result in overestimation of the true effects.CONCLUSIONS: The treatments labelled as TAU for depression were clinically and statistically heterogeneous. We demonstrated that a few patients benefited from TAU and a small number of patients suffered from worsened depressive symptoms at the short term. The results can be included in health-economic models that compare depression treatments to TAU.

Objectives: Previous studies have shown the effectiveness of guided Internetbasedinterventions for depression compared to control groups. It is often hypothesizedthat Internet-based treatments are associated with lower costs, becauseface-to-face time with therapist is reduced. The objective of this study was toconduct an individual-participant data meta-analysis (IPD-MA) evaluating the costeffectivenessof guided Internet-based interventions for depression compared tocontrols from a societal perspective. Methods: A systematic literature searchwas conducted in electronic databases from 2000 to January 1st 2017. Studieswere included if they were randomized controlled trials (RCTs) in which the costeffectivenessof a guided Internet-based intervention for depression was comparedto a control. Cost-effectiveness analyses were conducted for improvement in depressivesymptoms measured by CES-D, response to treatment, and Quality-AdjustedLife-Years (QALYs) at 8-weeks, 6-months, and 12-months follow-up. Results: IPD from five studies, including 1,426 participants were used. The guided Internet-basedinterventions were more costly than the controls, but not statistically significantlyso (e.g.12-months mean difference = € 406, 95%CI: -611 to 1,444). Cost-effectivenessacceptability curves indicated that high investments are needed to reach an acceptableprobability that the intervention is cost-effective compared to control for CES-Dand response to treatment (e.g., at 12-month follow-up the probability of being costeffectivewas 0.95 at a ceiling ratio of 2,000 € /point of improvement in CES-D score).For QALYs, the intervention’s probability of being cost-effective compared to controlwas low at the commonly accepted willingness-to-pay threshold (e.g., at 12-monthfollow-up the probability was 0.29 and 0.31 at a ceiling ratio of 24,000 and 35,000€ /QALY, respectively). Conclusions: Guided Internet-based interventions fordepression were not considered cost-effective compared to control. However, onlya minority of RCTs investigating the clinical effectiveness of guided Internet-basedinterventions also assessed cost-effectiveness. Therefore, it is important that futureRCTs measure resource use and productivity losses alongside clinical effectiveness.

BACKGROUND: Previous studies have demonstrated the effectiveness of Internet-based interventions for depression in comparison with usual care. However, evidence on the cost-effectiveness of these interventions when delivered in outpatient clinics is lacking. The aim of this study was to estimate the cost-effectiveness of an Internet-based problem-solving guided self-help intervention in comparison with enhanced usual care for outpatients on a waiting list for face-to-face treatment for major depression. After the waiting list period, participants from both groups received the same treatment at outpatient clinics.METHODS: An economic evaluation was performed alongside a randomized controlled trial with 12 months follow-up. Outcomes were improvement in depressive symptom severity (measured by CES-D), response to treatment and Quality-Adjusted Life-Years (QALYs). Statistical uncertainty around cost differences and incremental cost-effectiveness ratios were estimated using bootstrapping.RESULTS: Mean societal costs for the intervention group were €1579 higher than in usual care, but this was not statistically significant (95% CI - 1395 to 4382). Cost-effectiveness acceptability curves showed that the maximum probability of the intervention being cost-effective in comparison with usual care was 0.57 at a ceiling ratio of €15,000/additional point of improvement in CES-D, and 0.25 and 0.30 for an additional response to treatment and an extra QALY respectively, at a ceiling ratio of €30,000. Sensitivity analysis showed that from a mental healthcare provider perspective the probability of the intervention being cost-effective was 0.68 for a ceiling ratio of 0 €/additional unit of effect for the CES-D score, response to treatment and QALYs. As the ceiling ratio increased this probability decreased, because the mean costs in the intervention group were lower than the mean costs in the usual care group.LIMITATIONS: The patients in the intervention group showed low adherence to the Internet-based treatment. It is possible that greater adherence would have led to larger clinical effects.CONCLUSIONS: Offering an Internet-based intervention to depressed outpatients on waiting list for face-to-face treatment was not considered cost-effective in comparison with enhanced usual care from a societal perspective. There was a high probability of the intervention being cost-effective in comparison with enhanced usual care from the perspective of the mental healthcare provider.

Introduction: Multiple myeloma (MM) is associated with high healthcare resource utilisation. Better understanding of the hospital use by patients with MM is needed to plan future resource allocation to care for these patients. The aim of this study was to characterise the hospital use by patients with MM in the English National Health Service (NHS). Methods: Routinely-collected aggregate hospital admissions data from patients with MM were used from all 451 hospital trusts in the English NHS. This included elective and non-elective hospital admissions from April 1st 2014 to March 31st 2018. Patients were identified using the ICD-10 code for MM (C90.0) as either primary or secondary diagnosis. The number of admissions, number of patients, procedures, and total NHS hospital costs (based on Healthcare Resource Groups and NHS national tariff) were extracted alongside data to identify what percentage of the total NHS admissions are related to MM. Elective admissions were defined as admissions where the decision to admit preceded the time of the actual admission. Results: There were 754,345 admission records reported during the period of analysis from 17,555 women and 24,290 men. Of these, 675,400 (89%) were elective and 78,945 non-elective admissions. The total cost during the period analysed was £183,389,143 for elective and £227,650,088 for non-elective admissions. For elective admissions, 65% of the costs were for day-cases. Despite non-elective admissions constituting only 11% of all admissions, they accounted for 55% of the total hospitalisation costs. Over the period of analysis, elective admissions increased in average by 4.5% per year whilst the average yearly increase in costs was 1.5%; for non-elective hospitalisations, these figures were 4.1% and 9.0%, respectively (Figure). Of the total number of non-elective admissions over the study period, 58% were by men. Most of the procedures for elective admissions were related to chemotherapy and for non-elective ones the majority regarded radiology. While only 0.2% of all patients admitted to the NHS between April 2014 and March 2018 had a MM code, they accounted for 1% of all admission records and 0.5% of all inpatient NHS costs. During this period, patients with MM had on average 19 elective and 3 non-elective admissions per year, compared to 3 elective and 2 non-elective admissions per year per person for all patients admitted to the NHS. Conclusions: MM is associated with a large number of hospital admissions in the English NHS, relative to the low incidence of the disease. While the majority of the hospital admissions are elective, non-elective admissions accounted for the majority of costs. The impact of non-elective admissions should be included when assessing the economic burden of MM and the benefits from novel therapies. Further research is needed to understand the timing of non-elective admissions in the natural history of MM. Disclosures Ramasamy: Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Nador:Amgen: Research Funding. Kishore:Celgene: Honoraria; Takeda: Honoraria, Other: travel support. Rabin:Novartis: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau; Janssen: Consultancy, Other: Travel support, Speakers Bureau; Takeda: Consultancy, Other: Travel support , Speakers Bureau; Celgene: Speakers Bureau. Yong:Janssen: Honoraria, Speakers Bureau; Amgen: Honoraria, Research Funding, Speakers Bureau; Takeda: Speakers Bureau; Celgene: Honoraria. Ashcroft:Amgen: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau; Celgene Corporation: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Amaris Medical: Consultancy, Honoraria. Bowcock:Janssen: Honoraria; Takeda: Honoraria; Amgen: Honoraria; Takeda: Consultancy. Drayson:Abingdon Health: Equity Ownership, Membership on an entity's Board of Directors or advisory committees.

Objectives: Male obesity is on the rise, but few men take part in weight loss programmes. One reason for this could be the absence of gender‐sensitised interventions for men. This study aims to investigate the long‐term cost‐effectiveness of EuroFIT, a gender sensitised weight loss and healthy living programme for male football (soccer) fans, compared to waiting list. Methods: A Markov model was developed to represent the benefits of physical activity in reducing the incidence of 4 chronic health conditions (colorectal cancer, type 2 diabetes, coronary heart disease and stroke) and mortality. The model employed a 5‐year time horizon from a societal perspective and measured health gains in terms of quality adjusted life years (QALYs). Data was obtained from 4 pragmatic randomised controlled trials evaluating EuroFIT conducted in England, Netherlands, Portugal and Norway, epidemiological and cohort studies, and reviews of the literature. Parameter uncertainty was assessed using deterministic and probabilistic sensitivity analysis. Uncertainty was presented using cost‐effectiveness acceptability curves (CEACs). A lifetime horizon was used in a sensitivity analysis. Results: Preliminary evidence suggests that over a 5‐year time horizon the average cost per participant for the EuroFIT group is €10 lower than for the waiting list, while the average QALY gain is 0.014. CEACs show that the probability of EuroFIT being cost‐effective compared to waiting list is 95% at 10,000 € per QALY. Sensitivity analysis suggests that EuroFIT is €16 cheaper and results in a gain of 0.2 QALYs compared to waiting list over a lifetime horizon with a 90% probability of being cost‐effective at 13,000 € per QALY. Conclusions: This analysis shows that EuroFIT,a gender sentisied weight loss and healthy living programme, is cost‐effective at 5 years and over a lifetime as compared to waiting list.