Multivariable fractional polynomial interaction to investigate continuous effect modifiers in a meta-analysis on higher versus lower PEEP for patients with ARDS

Nonlinear effects and effect modification at the participant-level in IPD meta-analysis part 2: methodological guidance is available

OBJECTIVES

To review methodological guidance for nonlinear covariate-outcome associations (NL), and linear effect modification and nonlinear effect modification (LEM and NLEM) at the participant level in individual participant data meta-analyses (IPDMAs) and their power requirements.

STUDY DESIGN AND SETTING

We searched Medline, Embase, Web of Science, Scopus, PsycINFO and the Cochrane Library to identify methodology publications on IPDMA of LEM, NL or NLEM (PROSPERO CRD42019126768).

RESULTS

Through screening 6,466 records we identified 54 potential articles of which 23 full texts were relevant. Nine further relevant publications were published before or after the literature search and were added. Of these 32 references, 21 articles considered LEM, 6 articles NL or NLEM and 6 articles described sample size calculations. A book described all four. Sample size may be calculated through simulation or closed form. Assessments of LEM or NLEM at the participant level need to be based on within-trial information alone. Nonlinearity (NL or NLEM) can be modeled using polynomials or splines to avoid categorization.

CONCLUSION

Detailed methodological guidance on IPDMA of effect modification at participant-level is available. However, methodology papers for sample size and nonlinearity are rarer and may not cover all scenarios. On these aspects, further guidance is needed.

Nonlinear effects and effect modification at the participant-level in IPD meta-analysis part 1: analysis methods are often substandard

OBJECTIVES

To review analysis methods used for linear effect modification (LEM), nonlinear covariate-outcome associations (NL) and nonlinear effect modification (NLEM) at the participant-level in individual participant data meta-analysis (IPDMA).

STUDY DESIGN AND SETTING

We searched Medline, Embase, Web of Science, Scopus, PsycINFO and the Cochrane Library to identify IPDMA of randomized controlled trials (PROSPERO CRD42019126768). We investigated if and how IPDMA examined LEM, NL and NLEM, including whether aggregation bias was addressed and if power was considered.

RESULTS

We screened 6,466 records, randomly sampled 207 and identified 100 IPDMA of LEM, NL or NLEM. Power for LEM was calculated a priori in 3 IPDMA. Of 100 IPDMA, 94 analyzed LEM, 4 NLEM and 8 NL. One-stage models were favoured for all three (56%, 100%, 50%, respectively). Two-stage models were used in 15%, 0% and 25% of IPDMA with unclear descriptions in 30%, 0% and 25%, respectively. Only 12% of one-stage LEM and NLEM IPDMA provided sufficient detail to confirm they had addressed aggregation bias.

CONCLUSION

Investigation of effect modification at the participant-level is common in IPDMA projects, but methods are often open to bias or lack detailed descriptions. Nonlinearity of continuous covariates and power of IPDMA are rarely assessed.

Investigating treatment-effect modification by a continuous covariate in IPD meta-analysis: an approach using fractional polynomials

BACKGROUND

In clinical trials, there is considerable interest in investigating whether a treatment effect is similar in all patients, or that one or more prognostic variables indicate a differential response to treatment. To examine this, a continuous predictor is usually categorised into groups according to one or more cutpoints. Several weaknesses of categorization are well known. To avoid the disadvantages of cutpoints and to retain full information, it is preferable to keep continuous variables continuous in the analysis. To handle this issue, the Subpopulation Treatment Effect Pattern Plot (STEPP) was proposed about two decades ago, followed by the multivariable fractional polynomial interaction (MFPI) approach. Provided individual patient data (IPD) from several studies are available, it is possible to investigate for treatment heterogeneity with meta-analysis techniques. Meta-STEPP was recently proposed and in patients with primary breast cancer an interaction of estrogen receptors with chemotherapy was investigated in eight randomized controlled trials (RCTs).

METHODS

We use data from eight randomized controlled trials in breast cancer to illustrate issues from two main tasks. The first task is to derive a treatment effect function (TEF), that is, a measure of the treatment effect on the continuous scale of the covariate in the individual studies. The second is to conduct a meta-analysis of the continuous TEFs from the eight studies by applying pointwise averaging to obtain a mean function. We denote the method metaTEF. To improve reporting of available data and all steps of the analysis we introduce a three-part profile called MethProf-MA.

RESULTS

Although there are considerable differences between the studies (populations with large differences in prognosis, sample size, effective sample size, length of follow up, proportion of patients with very low estrogen receptor values) our results provide clear evidence of an interaction, irrespective of the choice of the FP function and random or fixed effect models.

CONCLUSIONS

In contrast to cutpoint-based analyses, metaTEF retains the full information from continuous covariates and avoids several critical issues when performing IPD meta-analyses of continuous effect modifiers in randomised trials. Early experience suggests it is a promising approach.

TRIAL REGISTRATION

Not applicable.

Unusual Localization of Blood-Borne Loa loa Microfilariae in the Skin Depends on Microfilarial Density in the Blood: Implications for Onchocerciasis Diagnosis in Coendemic Areas

Background

The diagnostic gold standard for onchocerciasis relies on identification and enumeration of (skin-dwelling) Onchocerca volvulus microfilariae (mf) using the skin snip technique (SST). In a recent study, blood-borne Loa loa mf were found by SST in individuals heavily infected with L. loa, and microscopically misidentified as O. volvulus due to their superficially similar morphology. This study investigates the relationship between L. loa microfilarial density (Loa MFD) and the probability of testing SST positive.

Methods

A total of 1053 participants from the (onchocerciasis and loiasis coendemic) East Region in Cameroon were tested for (1) Loa MFD in blood samples, (2) O. volvulus presence by SST, and (3) Immunoglobulin (Ig) G4 antibody positivity to Ov16 by rapid diagnostic test (RDT). A Classification and Regression Tree (CART) model was used to perform a supervised classification of SST status and identify a Loa MFD threshold above which it is highly likely to find L. loa mf in skin snips.

Results

Of 1011 Ov16-negative individuals, 28 (2.8%) tested SST positive and 150 (14.8%) were L. loa positive. The range of Loa MFD was 0–85 200 mf/mL. The CART model subdivided the sample into 2 Loa MFD classes with a discrimination threshold of 4080 (95% CI, 2180–12 240) mf/mL. The probability of being SST positive exceeded 27% when Loa MFD was >4080 mf/mL.

Conclusions

The probability of finding L. loa mf by SST increases significantly with Loa MFD. Skin-snip polymerase chain reaction would be useful when monitoring onchocerciasis prevalence by SST in onchocerciasis–loiasis coendemic areas.

Airway Pressure Release Ventilation Mode Improves Circulatory and Respiratory Function in Patients After Cardiopulmonary Bypass, a Randomized Trial

Importance

Postoperative pulmonary complications and cardiovascular complications are major causes of morbidity, mortality, and resource utilization in cardiac surgery patients.

Objectives

To investigate the effects of airway pressure release ventilation (APRV) on respiration and hemodynamics in post cardiac surgery patients.

Main Outcomes and Measures

A single-center randomized control trial was performed. In total, 138 patients undergoing cardiopulmonary bypass were prospectively screened. Ultimately 39 patients met the inclusion criteria and were randomized into two groups: 19 patients were managed with pressure control ventilation (PCV) and 20 patients were managed with APRV. Respiratory mechanics after 4 h, hemodynamics within the first day, and Chest radiograph score (CRS) and blood gasses within the first three days were recorded and compared.

Results

A higher cardiac index (3.1 ± 0.7 vs. 2.8 ± 0.8 L⋅min^–1⋅m²; p < 0.05), and shock volume index (35.4 ± 9.2 vs. 33.1 ± 9.7 ml m^–2; p < 0.05) were also observed in the APRV group after 4 h as well as within the first day (p < 0.05). Compared to the PCV group, the PaO2/FiO₂ was significantly higher after 4 h in patients of APRV group (340 ± 97 vs. 301 ± 82, p < 0.05) and within the first three days (p < 0.05) in the APRV group. CRS revealed less overall lung injury in the APRV group (p < 0.001). The duration of mechanical ventilation and ICU length of stay were not significantly (p = 0.248 and 0.424, respectively).

Conclusions and Relevance

Compared to PCV, APRV may be associated with increased cardiac output improved oxygenation, and decreased lung injury in postoperative cardiac surgery patients.

High versus low positive end-expiratory pressure (PEEP) levels for mechanically ventilated adult patients with acute lung injury and acute respiratory distress syndrome

BACKGROUND

In patients with acute lung injury (ALI) and acute respiratory distress syndrome (ARDS), mortality remains high. These patients require mechanical ventilation, which has been associated with ventilator-induced lung injury. High levels of positive end-expiratory pressure (PEEP) could reduce this condition and improve patient survival. This is an updated version of the review first published in 2013.

OBJECTIVES

To assess the benefits and harms of high versus low levels of PEEP in adults with ALI and ARDS.

SEARCH METHODS

For our previous review, we searched databases from inception until 2013. For this updated review, we searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, LILACS, and the Web of Science from inception until May 2020. We also searched for ongoing trials (www.trialscentral.org; www.clinicaltrial.gov; www.controlled-trials.com), and we screened the reference lists of included studies.

SELECTION CRITERIA

We included randomised controlled trials that compared high versus low levels of PEEP in ALI and ARDS participants who were intubated and mechanically ventilated in intensive care for at least 24 hours.

DATA COLLECTION AND ANALYSIS

Two review authors assessed risk of bias and extracted data independently. We contacted investigators to identify additional published and unpublished studies. We used standard methodological procedures expected by Cochrane.

MAIN RESULTS

We included four new studies (1343 participants) in this review update. In total, we included 10 studies (3851 participants). We found evidence of risk of bias in six studies, and the remaining studies fulfilled all criteria for low risk of bias. In eight studies (3703 participants), a comparison was made between high and low levels of PEEP, with the same tidal volume in both groups. In the remaining two studies (148 participants), the tidal volume was different between high- and low-level groups. In the main analysis, we assessed mortality occurring before hospital discharge only in studies that compared high versus low PEEP, with the same tidal volume in both groups. Evidence suggests that high PEEP may result in little to no difference in mortality compared to low PEEP (risk ratio (RR) 0.97, 95% confidence interval (CI) 0.90 to 1.04; I² = 15%; 7 studies, 3640 participants; moderate-certainty evidence). In addition, high PEEP may result in little to no difference in barotrauma (RR 1.00, 95% CI 0.64 to 1.57; I² = 63%; 9 studies, 3791 participants; low-certainty evidence). High PEEP may improve oxygenation in patients up to the first and third days of mechanical ventilation (first day: mean difference (MD) 51.03, 95% CI 35.86 to 66.20; I² = 85%; 6 studies, 2594 participants; low-certainty evidence; third day: MD 50.32, 95% CI 34.92 to 65.72; I² = 83%; 6 studies, 2309 participants; low-certainty evidence) and probably improves oxygenation up to the seventh day (MD 28.52, 95% CI 20.82 to 36.21; I² = 0%; 5 studies, 1611 participants; moderate-certainty evidence). Evidence suggests that high PEEP results in little to no difference in the number of ventilator-free days (MD 0.45, 95% CI -2.02 to 2.92; I² = 81%; 3 studies, 1654 participants; low-certainty evidence). Available data were insufficient to pool the evidence for length of stay in the intensive care unit.

AUTHORS' CONCLUSIONS

Moderate-certainty evidence shows that high levels compared to low levels of PEEP do not reduce mortality before hospital discharge. Low-certainty evidence suggests that high levels of PEEP result in little to no difference in the risk of barotrauma. Low-certainty evidence also suggests that high levels of PEEP improve oxygenation up to the first and third days of mechanical ventilation, and moderate-certainty evidence indicates that high levels of PEEP improve oxygenation up to the seventh day of mechanical ventilation. As in our previous review, we found clinical heterogeneity - mainly within participant characteristics and methods of titrating PEEP - that does not allow us to draw definitive conclusions regarding the use of high levels of PEEP in patients with ALI and ARDS. Further studies should aim to determine the appropriate method of using high levels of PEEP and the advantages and disadvantages associated with high levels of PEEP in different ARDS and ALI patient populations.

Individual participant data meta-analysis to examine interactions between treatment effect and participant-level covariates: Statistical recommendations for conduct and planning

Precision medicine research often searches for treatment‐covariate interactions, which refers to when a treatment effect (eg, measured as a mean difference, odds ratio, hazard ratio) changes across values of a participant‐level covariate (eg, age, gender, biomarker). Single trials do not usually have sufficient power to detect genuine treatment‐covariate interactions, which motivate the sharing of individual participant data (IPD) from multiple trials for meta‐analysis. Here, we provide statistical recommendations for conducting and planning an IPD meta‐analysis of randomized trials to examine treatment‐covariate interactions. For conduct, two‐stage and one‐stage statistical models are described, and we recommend: (i) interactions should be estimated directly, and not by calculating differences in meta‐analysis results for subgroups; (ii) interaction estimates should be based solely on within‐study information; (iii) continuous covariates and outcomes should be analyzed on their continuous scale; (iv) nonlinear relationships should be examined for continuous covariates, using a multivariate meta‐analysis of the trend (eg, using restricted cubic spline functions); and (v) translation of interactions into clinical practice is nontrivial, requiring individualized treatment effect prediction. For planning, we describe first why the decision to initiate an IPD meta‐analysis project should not be based on between‐study heterogeneity in the overall treatment effect; and second, how to calculate the power of a potential IPD meta‐analysis project in advance of IPD collection, conditional on characteristics (eg, number of participants, standard deviation of covariates) of the trials (potentially) promising their IPD. Real IPD meta‐analysis projects are used for illustration throughout.

Meta-analysis of non-linear exposure-outcome relationships using individual participant data: A comparison of two methods

Non-linear exposure-outcome relationships such as between body mass index (BMI) and mortality are common. They are best explored as continuous functions using individual participant data from multiple studies. We explore two two-stage methods for meta-analysis of such relationships, where the confounder-adjusted relationship is first estimated in a non-linear regression model in each study, then combined across studies. The "metacurve" approach combines the estimated curves using multiple meta-analyses of the relative effect between a given exposure level and a reference level. The "mvmeta" approach combines the estimated model parameters in a single multivariate meta-analysis. Both methods allow the exposure-outcome relationship to differ across studies. Using theoretical arguments, we show that the methods differ most when covariate distributions differ across studies; using simulated data, we show that mvmeta gains precision but metacurve is more robust to model mis-specification. We then compare the two methods using data from the Emerging Risk Factors Collaboration on BMI, coronary heart disease events, and all-cause mortality (>80 cohorts, >18 000 events). For each outcome, we model BMI using fractional polynomials of degree 2 in each study, with adjustment for confounders. For metacurve, the powers defining the fractional polynomials may be study-specific or common across studies. For coronary heart disease, metacurve with common powers and mvmeta correctly identify a small increase in risk in the lowest levels of BMI, but metacurve with study-specific powers does not. For all-cause mortality, all methods identify a steep U-shape. The metacurve and mvmeta methods perform well in combining complex exposure-disease relationships across studies.

Update in Management of Severe Hypoxemic Respiratory Failure

Mortality related to severe-moderate and severe ARDS remains high. We searched the literature to update this topic. We defined severe hypoxemic respiratory failure as Pao₂/Fio₂ < 150 mm Hg (ie, severe-moderate and severe ARDS). For these patients, we support setting the ventilator to a tidal volume of 4 to 8 mL/kg predicted body weight (PBW), with plateau pressure (Pplat) ≤ 30 cm H₂O, and initial positive end-expiratory pressure (PEEP) of 10 to 12 cm H₂O. To promote alveolar recruitment, we propose increasing PEEP in increments of 2 to 3 cm provided that Pplat remains ≤ 30 cm H₂O and driving pressure does not increase. A fluid-restricted strategy is recommended, and nonrespiratory causes of hypoxemia should be considered. For patients who remain hypoxemic after PEEP optimization, neuromuscular blockade and prone positioning should be considered. Profound refractory hypoxemia (Pao₂/Fio₂ < 80 mm Hg) after PEEP titration is an indication to consider extracorporeal life support. This may necessitate early transfer to a center with expertise in these techniques. Inhaled vasodilators and nontraditional ventilator modes may improve oxygenation, but evidence for improved outcomes is weak.

High-Frequency Oscillatory Ventilation in Adults With ARDS: Past, Present, and Future

High-frequency oscillatory ventilation (HFOV) is a unique mode of mechanical ventilation that uses nonconventional gas exchange mechanisms to deliver ventilation at very low tidal volumes and high frequencies. The properties of HFOV make it a potentially ideal mode to prevent ventilator-induced lung injury in patients with ARDS. Despite a compelling physiological basis and promising experimental data, large randomized controlled trials have not detected an improvement in survival with the use of HFOV, and its use as an early lung-protective strategy in patients with ARDS may be harmful. Nevertheless, HFOV still has an important potential role in the management of refractory hypoxemia. Careful attention should be paid to right ventricular function and lung stress when applying HFOV. This review discusses the physiological principles, clinical evidence, practical applications, and future prospects for the use of HFOV in patients with ARDS.