12 research outputs found

    Prognostic factors for mental wellbeing in prostate cancer:A systematic review and meta-analysis

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    OBJECTIVES: To evaluate the evidence base for patient, oncological, and treatment prognostic factors associated with multiple mental wellbeing outcomes in prostate cancer patients.METHODS: We performed a literature search of MEDLINE, EMBASE, and CINAHL databases including studies evaluating patient, oncological, or treatment factors against one of five mental wellbeing outcomes; depression, anxiety, fear of cancer recurrence, masculinity, and body image perception. Data synthesis included a random effects meta-analysis for the prognostic effect of individual factors if sufficient homogenous data was available, with a structured narrative synthesis where this was not possible.RESULTS: A final 62 articles were included. Older age was associated with a reducing odds of depression (OR 0.97, p = 0.04), with little evidence of effect for other outcomes. Additionally, baseline mental health status was related to depression and increasing time since diagnosis was associated with reducing fear of recurrence, albeith with low certainty of evidence. However, few other patient or oncological factors demonstrated any coherent relationship with any wellbeing outcome. Androgen deprivation therapy was associated with increased depression (HR 1.65, 95% CI 1.41-1.92, p &lt; 0.01) and anxiety, however, little difference was seen between other treatment options. Overall, whilst numerous factors were identified, most were evaluated by single studies with few evaluating masculinity and body image outcomes.CONCLUSION: We highlight the existing evidence for prognostic factors in mental wellbeing outcomes in prostate cancer, allowing us to consider high-risk groups of patients for preventative and treatment measures. However, the current evidence is heterogenous with further work required exploring less conclusive factors and outcomes.</p

    Comparative physiological effects of antipsychotic drugs in children and young people: a network meta-analysis.

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    BACKGROUND The degree of physiological responses to individual antipsychotic drugs is unclear in children and adolescents. With network meta-analysis, we aimed to investigate the effects of various antipsychotic medications on physiological variables in children and adolescents with neuropsychiatric and neurodevelopmental conditions. METHODS For this network meta-analysis, we searched Medline, EMBASE, PsycINFO, Web of Science, and Scopus from database inception until Dec 22, 2023, and included randomised controlled trials comparing antipsychotics with placebo in children or adolescents younger than 18 years with any neuropsychiatric and neurodevelopmental condition. Primary outcomes were mean change from baseline to end of acute treatment in bodyweight, BMI, fasting glucose, total cholesterol, LDL cholesterol, HDL cholesterol, triglycerides, prolactin, heart rate, systolic blood pressure (SBP), and QT interval corrected for heart rate (QTc) for patients receiving either active treatment or placebo. For multigroup trials reporting several doses, we calculated a summary value for each physiological variable for all doses. After transitivity assessment, we fitted frequentist random-effects network meta-analyses for all comparisons in the network. A Kilim plot was used to summarise the results for all treatments and outcomes, providing information regarding the strength of the statistical evidence of treatment effects, using p values. Network heterogeneity was assessed with τ, risk of bias of individual trials was assessed with the Cochrane Collaboration's Tool for Assessing Risk of Bias, and the credibility of findings from each network meta-analysis was assessed with the Confidence in Network Meta-Analysis (CINEMA) app. This study is registered on PROSPERO (CRD42021274393). FINDINGS Of 6676 studies screened, 47 randomised controlled trials were included, which included 6500 children (mean age 13·29 years, SD 2·14) who received treatment for a median of 7 weeks (IQR 6-8) with either placebo (n=2134) or one of aripiprazole, asenapine, blonanserin, clozapine, haloperidol, lurasidone, molindone, olanzapine, paliperidone, pimozide, quetiapine, risperidone, or ziprasidone (n=4366). Mean differences for bodyweight change gain compared with placebo ranged from -2·00 kg (95% CI -3·61 to -0·39) with molindone to 5·60 kg (0·27 to 10·94) with haloperidol; BMI -0·70 kg/m2 (-1·21 to -0·19) with molindone to 2·03 kg/m2 (0·51 to 3·55) with quetiapine; total cholesterol -0·04 mmol/L (-0·39 to 0·31) with blonanserin to 0·35 mmol/L (0·17 to 0·53) with quetiapine; LDL cholesterol -0·12 mmol/L (-0·31 to 0·07) with risperidone or paliperidone to 0·17 mmol/L (-0·06 to 0·40) with olanzapine; HDL cholesterol 0·05 mmol/L (-0·19 to 0·30) with quetiapine to 0·48 mmol/L (0·18 to 0·78) with risperidone or paliperidone; triglycerides -0·03 mmol/L (-0·12 to 0·06) with lurasidone to 0·29 mmol/L (0·14 to 0·44) with olanzapine; fasting glucose from -0·09 mmol/L (-1·45 to 1·28) with blonanserin to 0·74 mmol/L (0·04 to 1·43) with quetiapine; prolactin from -2·83 ng/mL (-8·42 to 2·75) with aripiprazole to 26·40 ng/mL (21·13 to 31·67) with risperidone or paliperidone; heart rate from -0·20 bpm (-8·11 to 7·71) with ziprasidone to 12·42 bpm (3·83 to 21·01) with quetiapine; SBP from -3·40 mm Hg (-6·25 to -0·55) with ziprasidone to 10·04 mm Hg (5·56 to 14·51) with quetiapine; QTc from -0·61 ms (-1·47 to 0·26) with pimozide to 0·30 ms (-0·05 to 0·65) with ziprasidone. INTERPRETATION Children and adolescents show varied but clinically significant physiological responses to individual antipsychotic drugs. Treatment guidelines for children and adolescents with a range of neuropsychiatric and neurodevelopmental conditions should be updated to reflect each antipsychotic drug's distinct profile for associated metabolic changes, alterations in prolactin, and haemodynamic alterations. FUNDING UK Academy of Medical Sciences, Brain and Behaviour Research Foundation, UK National Institute of Health Research, Maudsley Charity, the Wellcome Trust, Medical Research Council, National Institute of Health and Care Research Biomedical Centre at King's College London and South London and Maudsley NHS Foundation Trust, the Italian Ministry of University and Research, the Italian National Recovery and Resilience Plan, and Swiss National Science Foundation

    Erratum to: Methods for evaluating medical tests and biomarkers

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    [This corrects the article DOI: 10.1186/s41512-016-0001-y.]

    Evidence synthesis to inform model-based cost-effectiveness evaluations of diagnostic tests: a methodological systematic review of health technology assessments

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    Background: Evaluations of diagnostic tests are challenging because of the indirect nature of their impact on patient outcomes. Model-based health economic evaluations of tests allow different types of evidence from various sources to be incorporated and enable cost-effectiveness estimates to be made beyond the duration of available study data. To parameterize a health-economic model fully, all the ways a test impacts on patient health must be quantified, including but not limited to diagnostic test accuracy. Methods: We assessed all UK NIHR HTA reports published May 2009-July 2015. Reports were included if they evaluated a diagnostic test, included a model-based health economic evaluation and included a systematic review and meta-analysis of test accuracy. From each eligible report we extracted information on the following topics: 1) what evidence aside from test accuracy was searched for and synthesised, 2) which methods were used to synthesise test accuracy evidence and how did the results inform the economic model, 3) how/whether threshold effects were explored, 4) how the potential dependency between multiple tests in a pathway was accounted for, and 5) for evaluations of tests targeted at the primary care setting, how evidence from differing healthcare settings was incorporated. Results: The bivariate or HSROC model was implemented in 20/22 reports that met all inclusion criteria. Test accuracy data for health economic modelling was obtained from meta-analyses completely in four reports, partially in fourteen reports and not at all in four reports. Only 2/7 reports that used a quantitative test gave clear threshold recommendations. All 22 reports explored the effect of uncertainty in accuracy parameters but most of those that used multiple tests did not allow for dependence between test results. 7/22 tests were potentially suitable for primary care but the majority found limited evidence on test accuracy in primary care settings. Conclusions: The uptake of appropriate meta-analysis methods for synthesising evidence on diagnostic test accuracy in UK NIHR HTAs has improved in recent years. Future research should focus on other evidence requirements for cost-effectiveness assessment, threshold effects for quantitative tests and the impact of multiple diagnostic tests

    Erratum to: Methods for evaluating medical tests and biomarkers

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    [This corrects the article DOI: 10.1186/s41512-016-0001-y.]

    Psycho-pharmacomicrobiomics: a systematic review and meta-analysis

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    Background: Understanding the interactions between the gut-microbiome and psychotropic medications interact ("psycho-pharmacomicrobiomics") could improve treatment stratification strategies in psychiatry. In this systematic review and meta-analysis, we explored first, whether psychotropics modify the gut-microbiome, and second, if the gut-microbiome affects the efficacy and tolerability of psychotropics. Methods: Following PRISMA guidelines, we searched (November 2022) for longitudinal and cross-sectional studies investigating the effect of psychotropics on the gut-microbiome. The primary outcome was the difference in diversity metrics (alpha and beta) before and after treatment with psychotropics (longitudinal studies), and in medicated compared to unmedicated individuals (cross-sectional studies). Secondary outcomes included the association between gut microbiome and efficacy and tolerability outcomes. Random effect meta-analyses were conducted on alpha diversity metrics, while beta diversity metrics were pooled using distance data extracted from graphs. Summary statistics: SMD and Higgins I2 for alpha diversity metrics, F and R values for beta diversity metrics. Results: Nineteen studies were included in our synthesis; twelve investigated antipsychotics and seven antidepressants. Results showed significant changes in alpha (4 studies; SMD: 0.12; 95% CI: 0.01 to 0.23; P=0.04; I2: 14%) and beta (F=15.59; R2:0.05; P<0.001) diversity metrics following treatment with antipsychotics and antidepressants, respectively. Altered gut microbiome composition at baseline was associated with tolerability and efficacy outcomes across studies, including response to antidepressants (2 studies; alpha diversity; SMD: 2.45; 95%CI: 0.50 - 4.40; P<0.001, I2: 0%). Conclusions: Treatment with psychotropic medications is associated with altered gut microbiome composition, in turn the gut microbiome may influence the efficacy and tolerability of these medications

    Imaging modalities for characterising T1 renal tumours: A systematic review and meta‐analysis of diagnostic accuracy

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    Abstract Objectives International guidelines recommend resection of suspected localised renal cell carcinoma (RCC), with surgical series showing benign pathology in 30%. Non‐invasive diagnostic tests to differentiate benign from malignant tumours are an unmet need. Our objective was to determine diagnostic accuracy of imaging modalities for detecting cancer in T1 renal tumours. Methods A systematic review was performed for reports of diagnostic accuracy of any imaging test compared to a reference standard of histopathology for T1 renal masses, from inception until January 2023. Twenty‐seven publications (including 2277 tumours in 2044 participants) were included in the systematic review, and nine in the meta‐analysis. Results Forest plots of sensitivity and specificity were produced for CT (seven records, 1118 participants), contrast‐enhanced ultrasound (seven records, 197 participants), [99mTc]Tc‐sestamibi SPECT/CT (five records, 263 participants), MRI (three records, 220 participants), [18F]FDG PET (four records, 43 participants), [68Ga]Ga‐PSMA‐11 PET (one record, 27 participants) and [111In]In‐girentuximab SPECT/CT (one record, eight participants). Meta‐analysis returned summary estimates of sensitivity and specificity for [99mTc]Tc‐sestamibi SPECT/CT of 88.6% (95% CI 82.7%–92.6%) and 77.0% (95% CI 63.0%–86.9%) and for [18F]FDG PET 53.5% (95% CI 1.6%–98.8%) and 62.5% (95% CI 14.0%–94.5%), respectively. A comparison hierarchical summary receiver operating characteristic (HSROC) model did not converge. Meta‐analysis was not performed for other imaging due to different thresholds for test positivity. Conclusion The optimal imaging strategy for T1 renal masses is not clear. [99mTc]Tc‐sestamibi SPECT/CT is an emerging tool, but further studies are required to inform its role in clinical practice. The field would benefit from standardisation of diagnostic thresholds for CT, MRI and contrast‐enhanced ultrasound to facilitate future meta‐analyses

    The role of the electroencephalogram (EEG) in determining the aetiology of catatonia: a systematic review and meta-analysis of diagnostic test accuracyResearch in context

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    Summary: Background: Catatonia is a psychomotor syndrome that has a wide range of aetiologies. Determining whether catatonia is due to a medical or psychiatric cause is important for directing treatment but is clinically challenging. We aimed to ascertain the performance of the electroencephalogram (EEG) in determining whether catatonia has a medical or psychiatric cause, conventionally defined. Methods: In this systematic review and meta-analysis of diagnostic test accuracy (PROSPERO CRD42021239027), Medline, EMBASE, PsycInfo, and AMED were searched from inception to May 11, 2022 for articles published in peer-reviewed journals that reported EEG findings in catatonia of a medical or psychiatric origin and were reported in English, French, or Italian. Eligible study types were clinical trials, cohort studies, case–control studies, cross-sectional studies, case series, and case reports. The reference standard was the final clinical diagnosis. Data extraction was conducted using individual patient-level data, where available, by two authors. We prespecified two types of studies to overcome the limitations anticipated in the data: larger studies (n ≥ 5), which were suitable for formal meta-analytic methods but generally lacked detailed information about participants, and smaller studies (n < 5), which were unsuitable for formal meta-analytic methods but had detailed individual patient level data, enabling additional sensitivity analyses. Risk of bias and applicability were assessed with the QUADAS-2 tool for larger studies, and with a published tool designed for case reports and series for smaller studies. The primary outcomes were sensitivity and specificity, which were derived using a bivariate mixed-effects regression model. Findings: 355 studies were included, spanning 707 patients. Of the 12 larger studies (5 cohort studies and 7 case series), 308 patients were included with a mean age of 48.2 (SD = 8.9) years. 85 (52.8%) were reported as male and 99 had catatonia due to a general medical condition. In the larger studies, we found that an abnormal EEG predicted a medical cause of catatonia with a sensitivity of 0.82 (95% CI 0.67–0.91) and a specificity of 0.66 (95% CI 0.45–0.82) with an I2 of 74% (95% CI 42–100%). The area under the summary ROC curve offered excellent discrimination (AUC = 0.83). The positive likelihood ratio was 2.4 (95% CI 1.4–4.1) and the negative likelihood ratio was 0.28 (95% CI 0.15–0.51). Only 5 studies had low concerns in terms of risk of bias and applicability, but a sensitivity analysis limited to these studies was similar to the main analysis. Among the 343 smaller studies, 399 patients were included, resulting in a sensitivity of 0.76 (95% CI 0.71–0.81), specificity of 0.67 (0.57–0.76) and AUC = 0.71 (95% CI 0.67–0.76). In multiple sensitivity analyses, the results were robust to the exclusion of reports of studies and individuals considered at high risk of bias. Features of limbic encephalitis, epileptiform discharges, focal abnormality, or status epilepticus were highly specific to medical catatonia, but features of encephalopathy had only moderate specificity and occurred in 23% of the cases of psychiatric catatonia in smaller studies. Interpretation: In cases of diagnostic uncertainty, the EEG should be used alongside other investigations to ascertain whether the underlying cause of catatonia is medical. The main limitation of this review is the differing thresholds for considering an EEG abnormal between studies. Funding: Wellcome Trust, NIHR Biomedical Research Centre at University College London Hospitals NHS Foundation Trust

    Cognitive domains affected post-COVID-19; a systematic review and meta-analysis.

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    Background and purposeThis review aims to characterize the pattern of post-COVID-19 cognitive impairment, allowing better prediction of impact on daily function to inform clinical management and rehabilitation.MethodsA systematic review and meta-analysis of neurocognitive sequelae following COVID-19 was conducted, following PRISMA-S guidelines. Studies were included if they reported domain-specific cognitive assessment in patients with COVID-19 at >4 weeks post-infection. Studies were deemed high-quality if they had >40 participants, utilized healthy controls, had low attrition rates and mitigated for confounders.ResultsFive of the seven primary Diagnostic and Statistical Manual of Mental Disorders (DSM-5) cognitive domains were assessed by enough high-quality studies to facilitate meta-analysis. Medium effect sizes indicating impairment in patients post-COVID-19 versus controls were seen across executive function (standardised mean difference (SMD) -0.45), learning and memory (SMD -0.55), complex attention (SMD -0.54) and language (SMD -0.54), with perceptual motor function appearing to be impacted to a greater degree (SMD -0.70). A narrative synthesis of the 56 low-quality studies also suggested no obvious pattern of impairment.ConclusionsThis review found moderate impairments across multiple domains of cognition in patients post-COVID-19, with no specific pattern. The reported literature was significantly heterogeneous, with a wide variety of cognitive tasks, small sample sizes and disparate initial disease severities limiting interpretability. The finding of consistent impairment across a range of cognitive tasks suggests broad, as opposed to domain-specific, brain dysfunction. Future studies should utilize a harmonized test battery to facilitate inter-study comparisons, whilst also accounting for the interactions between COVID-19, neurological sequelae and mental health, the interplay between which might explain cognitive impairment

    The impact of psychiatric comorbidity on Parkinson's disease outcomes:a systematic review and meta-analysis

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    Background: The burden of psychiatric symptoms in Parkinson's disease includes depression, anxiety, apathy, psychosis, and impulse control disorders. However, the relationship between psychiatric comorbidities and subsequent prognosis and neurological outcomes is not yet well understood. In this systematic review and meta-analysis, in individuals with Parkinson's disease, we aimed to characterise the association between specific psychiatric comorbidities and subsequent prognosis and neurological outcomes: cognitive impairment, death, disability, disease progression, falls or fractures and care home admission. Methods: We searched MEDLINE, Embase, PsycINFO and AMED up to 13th November 2023 for longitudinal observational studies which measured disease outcomes in people with Parkinson's disease, with and without specific psychiatric comorbidities, and a minimum of two authors extracted summary data. Studies of individuals with other parkinsonian conditions and those with outcome measures that had high overlap with psychiatric symptoms were excluded to ensure face validity. For each exposure-outcome pair, a random-effects meta-analysis was conducted based on standardised mean difference, using adjusted effect sizes–where available–in preference to unadjusted effect sizes. Study quality was assessed using the Newcastle–Ottawa Scale. Between-study heterogeneity was assessed using the I2 statistic and publication bias was assessed using funnel plots. PROSPERO Study registration number: CRD42022373072. Findings: There were 55 eligible studies for inclusion in meta-analysis (n = 165,828). Data on participants’ sex was available for 164,514, of whom 99,182 (60.3%) were male and 65,460 (39.7%) female. Study quality was mostly high (84%). Significant positive associations were found between psychosis and cognitive impairment (standardised mean difference [SMD] 0.44, [95% confidence interval [CI] 0.23–0.66], I2 30.9), psychosis and disease progression (SMD 0.46, [95% CI 0.12–0.80], I2 70.3%), depression and cognitive impairment (SMD 0.37 [95% CI 0.10–0.65], I2 27.1%), depression and disease progression (SMD 0.46 [95% CI 0.18–0.74], I2 52.2), depression and disability (SMD 0.42 [95% CI 0.25–0.60], I2 7.9%), and apathy and cognitive impairment (SMD 0.60 [95% CI 0.02–1.19], I2 27.9%). Between-study heterogeneity was moderately high. Interpretation: Psychosis, depression, and apathy in Parkinson's disease are all associated with at least one adverse outcome, including cognitive impairment, disease progression and disability. Whether this relationship is causal is not clear, but the mechanisms underlying these associations require exploration. Clinicians should consider these psychiatric comorbidities to be markers of a poorer prognosis in people with Parkinson's disease. Future studies should investigate the underlying mechanisms and which treatments for these comorbidities may affect Parkinson's disease outcomes. Funding:Wellcome Trust, UKNational Institute for Health Research (NIHR),National Institute for Health Research (NIHR)Biomedical Research Centre (BRC) atSouth London and Maudsley NHS Foundation Trust and King's College London,National Institute for Health Research (NIHR)Biomedical Research Centre (BRC) atUniversity College London Hospitals NHS Foundation Trust, National Brain Appeal.</p
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