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Background Acne vulgaris is a common skin condition that may cause psychosocial distress. There is evidence that topical treatment combinations, chemical peels and photochemical therapy (combined blue/red light) are effective for mild-to-moderate acne, while topical treatment combinations, oral antibiotics combined with topical treatments, oral isotretinoin and photodynamic therapy are most effective for moderate-to-severe acne. Effective treatments have varying costs. The National Institute for Health and Care Excellence (NICE) in England considers cost-effectiveness when producing national clinical, public health and social care guidance. Aim To assess the cost-effectiveness of treatments for mild-to-moderate and moderate-to-severe acne to inform relevant NICE guidance. Methods A decision–analytical model compared costs and quality-adjusted life-years (QALYs) of effective topical pharmacological, oral pharmacological, physical and combined treatments for mild-to-moderate and moderate-to-severe acne, from the perspective of the National Health Service in England. Effectiveness data were derived from a network meta-analysis. Other model input parameters were based on published sources, supplemented by expert opinion. Results All of the assessed treatments were more cost-effective than treatment with placebo (general practitioner visits without active treatment). For mild-to-moderate acne, topical treatment combinations and photochemical therapy (combined blue/red light) were most cost-effective. For moderate-to-severe acne, topical treatment combinations, oral antibiotics combined with topical treatments, and oral isotretinoin were the most cost-effective. Results showed uncertainty, as reflected in the wide confidence intervals around mean treatment rankings. Conclusion A range of treatments are cost-effective for the management of acne. Well-conducted studies are needed to examine the long-term clinical efficacy and cost-effectiveness of the full range of acne treatments.

Summary Background Various treatments for acne vulgaris exist, but little is known about their comparative effectiveness in relation to acne severity. Objectives To identify best treatments for mild-to-moderate and moderate-to-severe acne, as determined by clinician-assessed morphological features. Methods We undertook a systematic review and network meta-analysis of randomized controlled trials (RCTs) assessing topical pharmacological, oral pharmacological, physical and combined treatments for mild-to-moderate and moderate-to-severe acne, published up to May 2020. Outcomes included percentage change in total lesion count from baseline, treatment discontinuation for any reason, and discontinuation owing to side-effects. Risk of bias was assessed using the Cochrane risk-of-bias tool and bias adjustment models. Effects for treatments with ≥ 50 observations each compared with placebo are reported below. Results We included 179 RCTs with approximately 35 000 observations across 49 treatment classes. For mild-to-moderate acne, the most effective options for each treatment type were as follows: topical pharmacological – combined retinoid with benzoyl peroxide (BPO) [mean difference 26·16%, 95% credible interval (CrI) 16·75–35·36%]; physical – chemical peels, e.g. salicylic or mandelic acid (39·70%, 95% CrI 12·54–66·78%) and photochemical therapy (combined blue/red light) (35·36%, 95% CrI 17·75–53·08%). Oral pharmacological treatments (e.g. antibiotics, hormonal contraceptives) did not appear to be effective after bias adjustment. BPO and topical retinoids were less well tolerated than placebo. For moderate-to-severe acne, the most effective options for each treatment type were as follows: topical pharmacological – combined retinoid with lincosamide (clindamycin) (44·43%, 95% CrI 29·20–60·02%); oral pharmacological – isotretinoin of total cumulative dose ≥ 120 mg kg−1 per single course (58·09%, 95% CrI 36·99–79·29%); physical – photodynamic therapy (light therapy enhanced by a photosensitizing chemical) (40·45%, 95% CrI 26·17–54·11%); combined – BPO with topical retinoid and oral tetracycline (43·53%, 95% CrI 29·49–57·70%). Topical retinoids and oral tetracyclines were less well tolerated than placebo. The quality of included RCTs was moderate to very low, with evidence of inconsistency between direct and indirect evidence. Uncertainty in findings was high, in particular for chemical peels, photochemical therapy and photodynamic therapy. However, conclusions were robust to potential bias in the evidence. Conclusions Topical pharmacological treatment combinations, chemical peels and photochemical therapy were most effective for mild-to-moderate acne. Topical pharmacological treatment combinations, oral antibiotics combined with topical pharmacological treatments, oral isotretinoin and photodynamic therapy were most effective for moderate-to-severe acne. Further research is warranted for chemical peels, photochemical therapy and photodynamic therapy for which evidence was more limited. What is already known about this topic? Acne vulgaris is the eighth most common disease globally.Several topical, oral, physical and combined treatments for acne vulgaris exist.Network meta-analysis (NMA) synthesizes direct and indirect evidence and allows simultaneous inference for all treatments forming an evidence network.Previous NMAs have assessed a limited range of treatments for acne vulgaris and have not evaluated effectiveness of treatments for moderate-to-severe acne. What does this study add? For mild-to-moderate acne, topical treatment combinations, chemical peels, and photochemical therapy (combined blue/red light; blue light) are most effective.For moderate-to-severe acne, topical treatment combinations, oral antibiotics combined with topical treatments, oral isotretinoin and photodynamic therapy (light therapy enhanced by a photosensitizing chemical) are most effective.Based on these findings, along with further clinical and cost-effectiveness considerations, National Institute for Health and Care Excellence (NICE) guidance recommends, as first-line treatments, fixed topical treatment combinations for mild-to-moderate acne and fixed topical treatment combinations, or oral tetracyclines combined with topical treatments, for moderate-to-severe acne.

Randomised controlled trials of cancer treatments typically report progression free survival (PFS) and overall survival (OS) outcomes. Existing methods to synthesise evidence on PFS and OS either rely on the proportional hazards assumption or make parametric assumptions which may not capture the diverse survival curve shapes across studies and treatments. Furthermore, PFS and OS are not independent: OS is the sum of PFS and post-progression survival (PPS). Our aim was to develop a non-parametric approach for jointly synthesising evidence from published Kaplan-Meier survival curves of PFS and OS without assumingproportional hazards. Restricted mean survival times (RMST) are estimated by the area under the survival curves (AUCs) up to a restricted follow-up time. The correlation between AUCs due to the constraint that OS>PFS is estimated using bootstrap re-sampling. Network meta-analysis models are given for RMST for PFS and PPS and ensure that OS=PFS + PPS. Both additive and multiplicative network meta-analysis models are presented to obtain relative treatment effects as either differences or ratios of RMST. The methods are illustrated with a networkmeta-analysis of treatments for Stage IIIA-N2 Non-Small Cell Lung Cancer.The approach has implications for health economic models of cancer treatments which require estimates of the mean time spent in the PFS and PPS health-states. The methods can be applied to a single time-to-event outcome, and so have wide applicability in any field where time-to-event outcomes are reported, the proportional hazards assumption is in doubt, and survival curve shapes differ across studies and interventions.

Statistical software for meta-analysis (MA) and network meta-analysis (NMA) have become indispensable for researchers. The aim of this chapter is to introduce key features of MA and NMA software to compare the effectiveness of interventions. Commonly used or routinely maintained statistical software are reviewed, including commercial and open-sourced programs such as Stata, R and Excel plug-ins. It does not provide a comprehensive overview of all features available in the software covered. Rather, it focuses on the essential features required to carry out an MA or NMA . This chapter begins with a review of key considerations when implementing an MA or NMA , then presents a summary of the software. Key features of each software option are discussed.

Objectives: This study reviews simulation studies of discrete choice experiments to determine (i) how survey design features affect statistical efficiency, (ii) and to appraise their reporting quality. Outcomes: Statistical efficiency was measured using relative design (D-) efficiency, D-optimality, or D-error. Methods: For this systematic survey, we searched Journal Storage (JSTOR), Since Direct, PubMed, and OVID which included a search within EMBASE. Searches were conducted up to year 2016 for simulation studies investigating the impact of DCE design features on statistical efficiency. Studies were screened and data were extracted independently and in duplicate. Results for each included study were summarized by design characteristic. Previously developed criteria for reporting quality of simulation studies were also adapted and applied to each included study. Results: Of 371 potentially relevant studies, 9 were found to be eligible, with several varying in study objectives. Statistical efficiency improved when increasing the number of choice tasks or alternatives; decreasing the number of attributes, attribute levels; using an unrestricted continuous “manipulator” attribute; using model-based approaches with covariates incorporating response behaviour; using sampling approaches that incorporate previous knowledge of response behaviour; incorporating heterogeneity in a model-based design; correctly specifying Bayesian priors; minimizing parameter prior variances; and using an appropriate method to create the DCE design for the research question. The simulation studies performed well in terms of reporting quality. Improvement is needed in regards to clearly specifying study objectives, number of failures, random number generators, starting seeds, and the software used. Conclusion: These results identify the best approaches to structure a DCE. An investigator can manipulate design characteristics to help reduce response burden and increase statistical efficiency. Since studies varied in their objectives, conclusions were made on several design characteristics, however, the validity of each conclusion was limited. Further research should be conducted to explore all conclusions in various design settings and scenarios. Additional reviews to explore other statistical efficiency outcomes and databases can also be performed to enhance the conclusions identified from this review. Keywords: Discrete choice experiment, Systematic survey, Statistical efficiency, Relative D-efficiency, Relative D-error

Objective To statistically compare and evaluate commonly used methods of estimating reference intervals and to determine which method is best based on characteristics of the distribution of various data sets. Design and methods Three approaches for estimating reference intervals, i.e. parametric, non-parametric, and robust, were compared with simulated Gaussian and non-Gaussian data. The hierarchy of the performances of each method was examined based on bias and measures of precision. The findings of the simulation study were illustrated through real data sets. Results In all Gaussian scenarios, the parametric approach provided the least biased and most precise estimates. In non-Gaussian scenarios, no single method provided the least biased and most precise estimates for both limits of a reference interval across all sample sizes, although the non-parametric approach performed the best for most scenarios. The hierarchy of the performances of the three methods was only impacted by sample size and skewness. Differences between reference interval estimates established by the three methods were inflated by variability. Conclusions Whenever possible, laboratories should attempt to transform data to a Gaussian distribution and use the parametric approach to obtain the most optimal reference intervals. When this is not possible, laboratories should consider sample size and skewness as factors in their choice of reference interval estimation method. The consequences of false positives or false negatives may also serve as factors in this decision.

Background Comprehensive geriatric assessment (CGA) is an integrated model of care involving a geriatrician and an interdisciplinary team and can prioritize and manage complex health needs of older adults with multimorbidity. CGAs differ across healthcare settings, ranging from shared care conducted in primary care settings to specialized inpatient units in acute care. Models of care involving geriatricians vary across healthcare settings, and it is unclear which CGA model is most effective. Our objective is to conduct a systematic review and network meta-analysis (NMA) to examine the comparative effectiveness of various geriatrician-led CGAs and to identify which models improve patient and healthcare system level outcomes. Methods An integrated knowledge translation approach will be used and knowledge users (KUs) including patients, caregivers, geriatricians, and healthcare policymakers will be involved throughout the review. Electronic databases including MEDLINE, EMBASE, Cochrane library, and Ageline will be searched from inception to November 2016 to identify relevant studies. Randomized controlled trials of older adults (≥65 years of age) that examine geriatrician-led CGAs compared to any intervention will be included. Primary and secondary outcomes will be selected by KUs to ensure the results are relevant to their decision-making. Two reviewers will independently screen the search results, extract data, and assess risk of bias. Data will be synthesized using an NMA to allow for multiple comparisons using direct (head-to-head) as well as indirect evidence. Interventions will be ranked according to their effectiveness using surface under the cumulative ranking curve (SUCRA). Discussion As the proportion of older adults grows worldwide, the demand for specialized geriatric services that help manage complex health needs of older adults with multimorbidity will increase in many countries. Results from this systematic review and NMA will enhance decision-making and the efficient allocation of scarce geriatric resources. Moreover, active involvement of KUs throughout the review process will ensure the results are relevant to different levels of decision-making. Systematic review registration PROSPERO CRD42014014008 Electronic supplementary material The online version of this article (doi:10.1186/s13643-017-0460-4) contains supplementary material, which is available to authorized users.

ObjectiveTo provide a framework for quantifying the robustness of treatment ranks based on Surface Under the Cumulative RAnking curve (SUCRA) in network meta-analysis (NMA) and investigating potential factors associated with lack of robustness.MethodsWe propose the use of Cohen’s kappa to quantify the agreement between SUCRA-based treatment ranks estimated through NMA of a complete data set and a subset of it. We illustrate our approach using five published NMA data sets, where robustness was assessed by removing studies one at a time.ResultsOverall, SUCRA-based treatment ranks were robust to individual studies in the five data sets we considered. We observed more incidences of disagreement between ranks in the networks with larger numbers of treatments. Most treatments moved only one or two ranks up or down. The lowest quadratic weighted kappa estimate observed across all networks was in the network with the smallest number of treatments (4), where weighted kappa=40%. In the network with the largest number of treatments (12), the lowest observed quadratic weighted kappa=89%, reflecting a small shift in this network's treatment ranks overall. Preliminary observations suggest that a study’s size, the number of studies making a treatment comparison, and the agreement of a study’s estimated treatment effect(s) with those estimated by other studies making the same comparison(s) may explain the overall robustness of treatment ranks to studies.ConclusionsInvestigating robustness or sensitivity in an NMA may reveal outlying rank changes that are clinically or policy-relevant. Cohen’s kappa is a useful measure that permits investigation into study characteristics that may explain varying sensitivity to individual studies. However, this study presents a framework as a proof of concept and further investigation is required to identify potential factors associated with the robustness of treatment ranks using more extensive empirical evaluations.

Objectives To develop an accurate assay and establish the normal reference intervals for serum cortisol, corticosterone, 11-deoxycortisol, androstenedione, 21-hydroxyprogesterone, testosterone, 17-hydroxyprogesterone, and progesterone. These steroids are commonly used as biomarkers for the diagnosis and monitoring of endocrine diseases such as congenital adrenal hyperplasia. Appropriate age- and gender-stratified reference intervals are essential in accurate interpretation of steroid hormone levels. Design and methods The samples analyzed in this study were collected from healthy, ethnically diverse children in the Greater Toronto Area as part of the CALIPER program. A total of 337 serum samples from children between the ages of 0 and 18 years were analyzed. The concentrations were measured by using an LC–MS/MS method. The data were analyzed for outliers and age- and gender-specific partitions were established prior to establishing the 2.5th and 97.5th percentiles for the reference intervals. Results Reference intervals for all hormones required significant age-dependent stratification while testosterone and progesterone required additional sex-dependent stratification. Conclusions We report a sensitive, accurate and relatively fast LC–MS/MS method for the simultaneous measurement of eight steroid hormones. Detailed reference intervals partitioned based on both age and gender were also established for all eight steroid hormones.

Studies have demonstrated improved analytical performance of the Nova StatStrip glucose meter, but limited data is available on its clinical performance in critically ill neonates in the neonatal intensive care unit (NICU).A retrospective charge review was conducted on 651 neonates admitted to the NICU over 2 years. Demographics, sample collection information, and clinical details were recorded. Glucose measurements were performed at the bedside using either the Nova StraStrip or LifeScan SureStep Flexx meters as well as corresponding measurements of laboratory venous plasma glucose. Performance was analyzed by receiver operator characteristic (ROC) curves for detecting hypoglycemia and critical glucose levels.Linear regression analysis comparing StatStrip and laboratory venous plasma glucose samples demonstrated significantly tighter agreement (r(2)=0.7994) and accuracy (mean bias=0.13mmol/L) than SureStep (r(2)=0.6845 and mean bias=0.53mmol/L). StatStrip also showed improved sensitivity for detecting critical low glucose values ≤3.0mmol/L (80.9 vs 68.9%, p0.05). ROC curve analysis further demonstrated excellent performance of StatStrip at this cutoff with an AUC of 0.98. Overall, neonates were also tested significantly less frequently with the StatStrip meter by 24% compared to SureStep.Implementation of StatStrip led to better agreement with venous plasma glucose, improved detection of critical low glucose results, and more efficient test utilization. This study demonstrates the importance of accurate and sensitive glucose monitoring in the NICU.

Objectives This study aims to investigate current medical literature with focus on statistical methods used to construct pediatric reference intervals and identify potential gaps within the process of reference interval estimation. Design and methods A systematic review of methods was performed. Extensive search criteria were developed and search was conducted on Embase, Medline, and PubMed databases to identify relevant articles. The articles were further screened using predefined inclusion and exclusion criteria. The selected articles were then included in our final systematic review. Results Our review reveals that there are gaps within current methodology and reporting of pediatric reference intervals. Not all publications followed the Clinical and Laboratory Standards Institute (CLSI) guidelines, and there is a large variation in the methods used. Discrepancies particularly arose when reference intervals were calculated for partitions with small sample sizes. In addition, the dynamic nature of pediatric data was not mostly captured when certain partitioning techniques were used. Conclusions There are areas within the pediatric reference interval development process that need attention. Partitioning methods particularly need to be explored with the goals of reducing subjectivity and enabling researchers to capture the best representative partitions possible. Moreover, the complicated nature of pediatric data often limits the sample size available for each partition and appropriate methods need to be considered in such cases. Researchers are also strongly encouraged to accompany their reference limits with confidence intervals to show sampling variability and demonstrate precision of their limits. These issues exemplify the need for a pediatric specific guideline that outlines a standardized way of establishing reference intervals.

BACKGROUNDPediatric healthcare is critically dependent on the availability of accurate and precise laboratory biomarkers of pediatric disease, and on the availability of reference intervals to allow appropriate clinical interpretation. The development and growth of children profoundly influence normal circulating concentrations of biochemical markers and thus the respective reference intervals. There are currently substantial gaps in our knowledge of the influences of age, sex, and ethnicity on reference intervals. We report a comprehensive covariate-stratified reference interval database established from a healthy, nonhospitalized, and multiethnic pediatric population.METHODSHealthy children and adolescents (n = 2188, newborn to 18 years of age) were recruited from a multiethnic population with informed parental consent and were assessed from completed questionnaires and according to defined exclusion criteria. Whole-blood samples were collected for establishing age- and sex-stratified reference intervals for 40 serum biochemical markers (serum chemistry, enzymes, lipids, proteins) on the Abbott ARCHITECT c8000 analyzer.RESULTSReference intervals were generated according to CLSI C28-A3 statistical guidelines. Caucasians, East Asians, and South Asian participants were evaluated with respect to the influence of ethnicity, and statistically significant differences were observed for 7 specific biomarkers.CONCLUSIONSThe establishment of a new comprehensive database of pediatric reference intervals is part of the Canadian Laboratory Initiative in Pediatric Reference Intervals (CALIPER). It should assist laboratorians and pediatricians in interpreting test results more accurately and thereby lead to improved diagnosis of childhood diseases and reduced patient risk. The database will also be of global benefit once reference intervals are validated in transference studies with other analytical platforms and local populations, as recommended by the CLSI.