Lisa Askie

Duration of Chemotherapy for Advanced Non–Small-Cell Lung Cancer: A Systematic Review and Meta-Analysis of Randomized Trials

PURPOSE To determine if it is preferable to extend chemotherapy beyond a standard number of cycles in patients receiving first-line chemotherapy for advanced non-small-cell lung cancer. METHODS We searched biomedical literature databases and conference proceedings for randomized controlled trials (RCTs) comparing a defined number of cycles with continuation of the same chemotherapy until disease progression, a larger defined number of cycles of identical chemotherapy, and a defined number of cycles of identical initial chemotherapy followed by additional cycles of an alternative chemotherapy. Meta-analysis was performed using the fixed effect model. The primary outcome was overall survival (OS); secondary outcomes included progression-free survival (PFS), adverse events (AE), and health-related quality of life (HRQL). RESULTS We found 13 RCTs including 3,027 patients. Extending chemotherapy improved PFS substantially (hazard ratio [HR], 0.75; 95% CI, 0.69 to 0.81; P < .00001) and OS modestly (HR, 0.92; 95% CI, 0.86 to 0.99; P = .03). Subgroup analysis revealed that effects on PFS were greater for trials extending chemotherapy with third-generation regimens rather than older regimens (HR, 0.70 interaction v 0.92 interaction; P = .003). Extending chemotherapy was associated with more frequent AE in all trials where it was reported and impaired HRQL in two of seven trials. CONCLUSION Extending chemotherapy, particularly with a third-generation regimen, improved PFS substantially, but OS less so. Future trials should test extending treatment with more effective and/or better-tolerated agents.

Statistical Analysis of Individual Participant Data Meta-Analyses: A Comparison of Methods and Recommendations for Practice

Background Individual participant data (IPD) meta-analyses that obtain “raw” data from studies rather than summary data typically adopt a “two-stage” approach to analysis whereby IPD within trials generate summary measures, which are combined using standard meta-analytical methods. Recently, a range of “one-stage” approaches which combine all individual participant data in a single meta-analysis have been suggested as providing a more powerful and flexible approach. However, they are more complex to implement and require statistical support. This study uses a dataset to compare “two-stage” and “one-stage” models of varying complexity, to ascertain whether results obtained from the approaches differ in a clinically meaningful way. Methods and Findings We included data from 24 randomised controlled trials, evaluating antiplatelet agents, for the prevention of pre-eclampsia in pregnancy. We performed two-stage and one-stage IPD meta-analyses to estimate overall treatment effect and to explore potential treatment interactions whereby particular types of women and their babies might benefit differentially from receiving antiplatelets. Two-stage and one-stage approaches gave similar results, showing a benefit of using anti-platelets (Relative risk 0.90, 95% CI 0.84 to 0.97). Neither approach suggested that any particular type of women benefited more or less from antiplatelets. There were no material differences in results between different types of one-stage model. Conclusions For these data, two-stage and one-stage approaches to analysis produce similar results. Although one-stage models offer a flexible environment for exploring model structure and are useful where across study patterns relating to types of participant, intervention and outcome mask similar relationships within trials, the additional insights provided by their usage may not outweigh the costs of statistical support for routine application in syntheses of randomised controlled trials. Researchers considering undertaking an IPD meta-analysis should not necessarily be deterred by a perceived need for sophisticated statistical methods when combining information from large randomised trials.

Antiplatelet therapy before or after 16 weeks' gestation for preventing preeclampsia: an individual participant data meta-analysis.

BACKGROUND: The optimum time for commencing antiplatelet therapy for the prevention of preeclampsia and its complications is unclear. Aggregate data meta‐analyses suggest that aspirin is more effective if given prior to 16 weeks’ gestation, but data are limited because of an inability to place women in the correct gestational age subgroup from relevant trials. OBJECTIVE: The objective of the study was to use the large existing individual participant data set from the Perinatal Antiplatelet Review of International Studies Collaboration to assess whether the treatment effects of antiplatelet agents on preeclampsia and its complications vary based on whether treatment is started before or after 16 weeks’ gestation. STUDY DESIGN: A meta‐analysis of individual participant data including 32,217 women and 32,819 babies recruited to 31 randomized trials comparing low‐dose aspirin or other antiplatelet agents with placebo or no treatment for the prevention of preeclampsia has been published previously. Using this existing data set, we performed a prespecified subgroup analysis based on gestation at randomization to antiplatelet agents before 16 weeks, compared with at or after 16 weeks, for 4 of the main outcomes prespecified in the Perinatal Antiplatelet Review of International Studies protocol: preeclampsia, death of baby, preterm birth before 34 weeks, and small‐for‐gestational‐age baby. Individual participant data for the subgroups were combined in a meta‐analysis using RevMan software. Heterogeneity was assessed with the I2 statistic. The χ2 test for interaction was used to assess statistically significant (P < .05) differences in treatment effect between subgroups. RESULTS: There was no significant difference in the effects of antiplatelet therapy for women randomized before 16 weeks’ gestation compared with those randomized at or after 16 weeks for any of the 4 prespecified outcomes: preeclampsia, relative risk, 0.90, (95% confidence interval, 0.79–1.03; 17 trials, 9241 women) for <16 weeks and relative risk, 0.90 (95% confidence interval, 0.83–0.98; 22 trials, 21,429 women) for ≥16 weeks (interaction test, P = .98); death of baby, relative risk, 0.89 (95% confidence interval, 0.73–1.09; 15 trials, 8626 women) for <16 weeks and relative risk, 0.92 (95% confidence interval, 0.79–1.07; 21 trials, 22,336 women) for ≥16 weeks (interaction test, P = .80); preterm birth prior to 34 weeks, relative risk, 0.90 (95% confidence interval, 0.77–1.04; 19 trials, 9155 women) for <16 weeks and relative risk, 0.91 (95% confidence interval, 0.82–1.00; 25 trials, 22,117 women) for ≥16 weeks (interaction test, P = .91); and small‐for‐gestational‐age baby, relative risk, 0.76 (95% confidence interval, 0.61–0.94; 13 trials, 6393 women) for <16 weeks and relative risk, 0.95 (95% confidence interval, 0.84–1.08; 18 trials, 14,996 women) for ≥16 weeks (interaction test, P = .08). CONCLUSION: The effect of low‐dose aspirin and other antiplatelet agents on preeclampsia and its complications is consistent, regardless of whether treatment is started before or after 16 weeks’ gestation. Women at an increased risk of preeclampsia should be offered antiplatelet therapy, regardless of whether they are first seen before or after 16 weeks’ gestation.

The Early Prevention of Obesity in CHildren (EPOCH) Collaboration - an Individual Patient Data Prospective Meta-Analysis

BackgroundEfforts to prevent the development of overweight and obesity have increasingly focused early in the life course as we recognise that both metabolic and behavioural patterns are often established within the first few years of life. Randomised controlled trials (RCTs) of interventions are even more powerful when, with forethought, they are synthesised into an individual patient data (IPD) prospective meta-analysis (PMA). An IPD PMA is a unique research design where several trials are identified for inclusion in an analysis before any of the individual trial results become known and the data are provided for each randomised patient. This methodology minimises the publication and selection bias often associated with a retrospective meta-analysis by allowing hypotheses, analysis methods and selection criteria to be specified a priori.Methods/DesignThe Early Prevention of Obesity in CHildren (EPOCH) Collaboration was formed in 2009. The main objective of the EPOCH Collaboration is to determine if early intervention for childhood obesity impacts on body mass index (BMI) z scores at age 18-24 months. Additional research questions will focus on whether early intervention has an impact on childrens dietary quality, TV viewing time, duration of breastfeeding and parenting styles. This protocol includes the hypotheses, inclusion criteria and outcome measures to be used in the IPD PMA. The sample size of the combined dataset at final outcome assessment (approximately 1800 infants) will allow greater precision when exploring differences in the effect of early intervention with respect to pre-specified participant- and intervention-level characteristics.DiscussionFinalisation of the data collection procedures and analysis plans will be complete by the end of 2010. Data collection and analysis will occur during 2011-2012 and results should be available by 2013.Trial registration numberACTRN12610000789066

Delayed versus Immediate Cord Clamping in Preterm Infants

Background The preferred timing of umbilical‐cord clamping in preterm infants is unclear. Methods We randomly assigned fetuses from women who were expected to deliver before 30 weeks of gestation to either immediate clamping of the umbilical cord (≤10 seconds after delivery) or delayed clamping (≥60 seconds after delivery). The primary composite outcome was death or major morbidity (defined as severe brain injury on postnatal ultrasonography, severe retinopathy of prematurity, necrotizing enterocolitis, or late‐onset sepsis) by 36 weeks of postmenstrual age. Analyses were performed on an intention‐to‐treat basis, accounting for multiple births. Results Of 1634 fetuses that underwent randomization, 1566 were born alive before 30 weeks of gestation; of these, 782 were assigned to immediate cord clamping and 784 to delayed cord clamping. The median time between delivery and cord clamping was 5 seconds and 60 seconds in the respective groups. Complete data on the primary outcome were available for 1497 infants (95.6%). There was no significant difference in the incidence of the primary outcome between infants assigned to delayed clamping (37.0%) and those assigned to immediate clamping (37.2%) (relative risk, 1.00; 95% confidence interval, 0.88 to 1.13; P=0.96). The mortality was 6.4% in the delayed‐clamping group and 9.0% in the immediate‐clamping group (P=0.03 in unadjusted analyses; P=0.39 after post hoc adjustment for multiple secondary outcomes). There were no significant differences between the two groups in the incidences of chronic lung disease or other major morbidities. Conclusions Among preterm infants, delayed cord clamping did not result in a lower incidence of the combined outcome of death or major morbidity at 36 weeks of gestation than immediate cord clamping. (Funded by the Australian National Health and Medical Research Council [NHMRC] and the NHMRC Clinical Trials Centre; APTS Australian and New Zealand Clinical Trials Registry number, ACTRN12610000633088.)

Optimal oxygen saturations in preterm infants: a moving target.

Purpose of review New evidence is emerging to address the continued uncertainty regarding the optimal range to target oxygen saturation levels in preterm infants. Recent findings A recently published systematic review summarized the existing evidence for currently used oxygen saturation targets in preterm infants and highlighted the paucity of randomized trials addressing this topic. It appears that higher oxygen saturation levels increase the risk of severe retinopathy of prematurity and pulmonary morbidities. However, data regarding the effects of various target ranges on early mortality and long-term neurodevelopmental outcomes are lacking. A collaborative group of investigators from five independent randomized trials was established to answer this question definitively. Although the final analysis will not be available until 2014, interim results from four of these trials revealed an increase in early mortality when the lower oxygen saturation range is targeted. At present, it may be prudent not to target oxygen saturation levels below 90%. Whatever the optimal range, consistently maintaining the newborns oxygen saturation levels within target proves an additional challenge for providers. Both technological advancements and optimized patient--caregiver ratios may be useful in achieving targeted oxygen saturation goals. Summary Defining and maintaining optimal oxygen saturations in preterm infants remains a challenge for clinicians caring for preterm infants. However, ongoing investigative collaborations may soon provide guidance.

Clinical prediction models for bronchopulmonary dysplasia: a systematic review and external validation study

BackgroundBronchopulmonary dysplasia (BPD) is a common complication of preterm birth. Very different models using clinical parameters at an early postnatal age to predict BPD have been developed with little extensive quantitative validation. The objective of this study is to review and validate clinical prediction models for BPD.MethodsWe searched the main electronic databases and abstracts from annual meetings. The STROBE instrument was used to assess the methodological quality. External validation of the retrieved models was performed using an individual patient dataset of 3229 patients at risk for BPD. Receiver operating characteristic curves were used to assess discrimination for each model by calculating the area under the curve (AUC). Calibration was assessed for the best discriminating models by visually comparing predicted and observed BPD probabilities.ResultsWe identified 26 clinical prediction models for BPD. Although the STROBE instrument judged the quality from moderate to excellent, only four models utilised external validation and none presented calibration of the predictive value. For 19 prediction models with variables matched to our dataset, the AUCs ranged from 0.50 to 0.76 for the outcome BPD. Only two of the five best discriminating models showed good calibration.ConclusionsExternal validation demonstrates that, except for two promising models, most existing clinical prediction models are poor to moderate predictors for BPD. To improve the predictive accuracy and identify preterm infants for future intervention studies aiming to reduce the risk of BPD, additional variables are required. Subsequently, that model should be externally validated using a proper impact analysis before its clinical implementation.

National and multinational prospective trial registers

Clinical trials are an essential source of scientifi c evidence on the safety and eff ectiveness of health interventions. Prospectively registering information about a trial before enrolling participants, tracking changes to that information via a publicly accessible audit trail, and reporting results on completion of the trial helps protect against reporting biases and over-optimistic conclusions about treatment benefi ts. Open-access registries should decrease wasteful duplication of research, promote more effi cient allocation of research funds, and ensure trial information is disseminated and incorporated into the appropriate body of evidence for clinical, funding, and ethical decision-making. The increased commitment to prospective trial registration and the establishment of trial registers has the potential to increase the number of duplicate registrations (panel). It has been argued that if duplicate trial registration is left unchecked, the integrity of trial registries may be compromised, which would falsely over-infl ate the number of trials and confuse users. Limiting the number of registries has been proposed as a possible mechanism to prevent duplicate trial registration. Despite these concerns, there are several compelling reasons why both national and multinational registers are important. National registers are ideally placed to promote, identify, and track clinical trials in a specifi c country. Such registers can fully integrate into local ethics and regulatory processes, which thus ensures complete and comprehensive registration of all trials in their region of infl uence. Such decentralised trial registration is essential to achieve a comprehensive global register of all clinical trials. A philosophical reason underpinning the need for national registers is that most national registers have been developed within specifi c political frameworks and policy makers value them as a source of national pride. It may therefore not be politically expedient to dismiss these registers or undermine their legitimacy. Multinational registers can be especially important in resource-poor settings where individual countries do not have the necessary resources to establish national registers. Such registers serve the needs of several neighbouring countries, usually with similar disease burdens. By sharing technical and operational resources, costs to individual countries can be reduced and promotion of registration can be streamlined across countries (eg, by working with established regulatory or inter-government organ isations, such as WHO/AFRO in Africa or the Pan American Health Organisation in Latin America). There is an urgent need, particularly in resource-poor countries, to improve the ability of researchers to do high-quality clinical trials. National and multi national registers are able to identify and meet the needs of these researchers, by ensuring that information on various aspects of study design is collected and checked on registration. At an operational level, national and multinational registers can customise the registration process to suit the needs of their particular users (eg, displaying information in the local language). It is essential that WHO’s International Clinical Trial Registry Platform continues to work closely with governments and multinational bodies that have the necessary

Is body fat percentage a better measure of undernutrition in newborns than birth weight percentiles

Background:Undernutrition in neonates increases the risk of serious morbidities. The objective of this study was to describe neonatal morbidity associated with low body fat percentage (BF%) and measure the number of undernourished neonates defined by BF% and compare this with birth weight percentiles (<10th).Methods:Eligibility included term (≥37 wk) neonates. BF% measurements were undertaken by air displacement plethysmography. Data on neonatal outcomes were extracted from medical records and used to develop a measure of neonatal morbidity. We assessed the association between neonatal morbidity and population-based birth weight percentiles compared with the BF% measurements.Results:Five hundred and eighty-one neonates were included. Low BF% was defined by 1 SD below the mean and identified in 73 per 1,000 live births. Neonatal morbidity was found in 3.4% of neonates. Birth weight percentile was associated with neonatal morbidity (odds ratio (OR): 1.03 (95% confidence interval (CI): 1.01, 1.05); P = <0.001). BF% was associated with a higher risk of neonatal morbidity (OR: 1.30 (95% CI: 1.15, 1.47); P = <0.001).Conclusion:In this population, measuring BF% is more closely associated with identification of neonates at risk of neonatal morbidity as compared with birth weight percentiles. BF% measurements could assist with identifying neonates who are appropriately grown yet undernourished and exclude small neonates not at risk.

Standard 4: Determining Adequate Sample Sizes

* Abbreviations: CINV — : chemotherapy-induced nausea and vomiting RCT — : randomized controlled trial RSV — : respiratory syncytial virus There are many challenges to be faced when conducting randomized controlled trials (RCTs) in pediatric research. One important challenge is the determination of an appropriate sample size. Recruiting more children than necessary risks unnecessary overexposure of children to an inferior treatment, whereas underestimating the sample required will lead to inconclusive or unreliable results. Both options pose important ethical dilemmas for the pediatric researcher. Reviews have concluded that sample size calculations are frequently based on inaccurate assumptions regarding the key pieces of information needed.1,2 For example, a recent “failed” pediatric RCT highlighted the commonly encountered problem of underestimating the SD of a continuous primary outcome variable.3 This leads to underestimation of the necessary sample size, inadequate statistical power, and, consequently, an unanswered study question. Similarly, an incorrect estimation of the frequency with which a dichotomous outcome, or event, occurs in the control group of a trial (known as the control or baseline event rate) will also lead to incorrect sample size estimation. This standards article uses a series of scenarios to assist pediatric researchers in not only determining an adequate trial sample size but also how to proceed when this sample size may be difficult to achieve. Recommendations for practice are summarized in Table 1. View this table: TABLE 1 Recommendations for Practice Methods to calculate adequate sample sizes are described for superiority, noninferiority, and cluster-randomized trials with various types of primary outcome variables, including continuous, dichotomous, or time-to-event data.4–10 In this article, we focus primarily on superiority trial designs with continuous or dichotomous outcomes. Information on noninferiority or equivalence designs, as well as on cluster-randomized designs, can be found in the literature.9,10 RCTs generally have many outcomes of interest, but the number of patients required (and the main statistical analysis) should be based on … Address correspondence to Martin Offringa, MD, PhD, Senior Scientist and Program Head, Child Health Evaluative Sciences, Research Institute, The Hospital for Sick Children, 555 University Ave, Toronto, Ontario, Canada M5G 1X8. E-mail: martin.offringa{at}sickkids.ca