Comments on 'standard and reference-based conditional mean imputation': Regulators and trial statisticians be aware!

Accurate frequentist performance of a method is desirable in confirmatory clinical trials, but is not sufficient on its own to justify the use of a missing data method. Reference-based conditional mean imputation, with variance estimation justified solely by its frequentist performance, has the surprising and undesirable property that the estimated variance becomes smaller the greater the number of missing observations; as explained under jump-to-reference it effectively forces the true treatment effect to be exactly zero for patients with missing data.

Assessing efficacy in non-inferiority trials with non-adherence to interventions: Are intention-to-treat and per-protocol analyses fit for purpose?

BACKGROUND: Non-inferiority trials comparing different active drugs are often subject to treatment non-adherence. Intention-to-treat (ITT) and per-protocol (PP) analyses have been advocated in such studies but are not guaranteed to be unbiased in the presence of differential non-adherence. METHODS: The REMoxTB trial evaluated two 4-month experimental regimens compared with a 6-month control regimen for newly diagnosed drug-susceptible TB. The primary endpoint was a composite unfavorable outcome of treatment failure or recurrence within 18 months post-randomization. We conducted a simulation study based on REMoxTB to assess the performance of statistical methods for handling non-adherence in non-inferiority trials, including: ITT and PP analyses, adjustment for observed adherence, multiple imputation (MI) of outcomes, inverse-probability-of-treatment weighting (IPTW), and a doubly-robust (DR) estimator. RESULTS: When non-adherence differed between trial arms, ITT, and PP analyses often resulted in non-trivial bias in the estimated treatment effect, which consequently under- or over-inflated the type I error rate. Adjustment for observed adherence led to similar issues, whereas the MI, IPTW and DR approaches were able to correct bias under most non-adherence scenarios; they could not always eliminate bias entirely in the presence of unobserved confounding. The IPTW and DR methods were generally unbiased and maintained desired type I error rates and statistical power. CONCLUSIONS: When non-adherence differs between trial arms, ITT and PP analyses can produce biased estimates of efficacy, potentially leading to the acceptance of inferior treatments or efficacious regimens being missed. IPTW and the DR estimator are relatively straightforward methods to supplement ITT and PP approaches.

Phylogenomics of Tetraopes longhorn beetles unravels their evolutionary history and biogeographic origins.

Tetraopes longhorn beetles are known for their resistance to milkweed plant toxins and their coevolutionary dynamics with milkweed plants (Asclepias). This association is considered a textbook example of coevolution, in which each species of Tetraopes is specialized to feed on one or a few species of Asclepias. A major challenge to investigating coevolutionary hypotheses and conducting molecular ecology studies lies in the limited understanding of the evolutionary history and biogeographical patterns of Tetraopes. By integrating genomic, morphological, paleontological, and geographical data, we present a robust phylogeny of Tetraopes and their relatives, using three inference methods with varying subsets of data, encompassing 2-12 thousand UCE loci. We elucidate the diversification patterns of Tetraopes species across major biogeographical regions and their colonization of the American continent. Our findings suggest that the genus originated in Central America approximately 21 million years ago during the Miocene and diversified from the Mid-Miocene to the Pleistocene. These events coincided with intense geological activity in Central America. Additionally, independent colonization events in North America occurred from the Late Miocene to the early Pleistocene, potentially contributing to the early diversification of the group. Our data suggest that a common ancestor of Tetraopini migrated into North America, likely facilitated by North Atlantic land bridges, while closely related tribes diverged in Asia and Europe during the Paleocene. Establishing a robust and densely sampled phylogeny of Tetraopes beetles provides a foundation for investigating micro- and macroevolutionary phenomena, including clinal variation, coevolution, and detoxification mechanisms in this ecologically important group.

Getting our ducks in a row: The need for data utility comparisons of healthcare systems data for clinical trials.

BACKGROUND: Better use of healthcare systems data, collected as part of interactions between patients and the healthcare system, could transform planning and conduct of randomised controlled trials. Multiple challenges to widespread use include whether healthcare systems data captures sufficiently well the data traditionally captured on case report forms. "Data Utility Comparison Studies" (DUCkS) assess the utility of healthcare systems data for RCTs by comparison to data collected by the trial. Despite their importance, there are few published UK examples of DUCkS. METHODS-AND-RESULTS: Building from ongoing and selected recent examples of UK-led DUCkS in the literature, we set out experience-based considerations for the conduct of future DUCkS. Developed through informal iterative discussions in many forums, considerations are offered for planning, protocol development, data, analysis and reporting, with comparisons at "patient-level" or "trial-level", depending on the item of interest and trial status. DISCUSSION: DUCkS could be a valuable tool in assessing where healthcare systems data can be used for trials and in which trial teams can play a leading role. There is a pressing need for trials to be more efficient in their delivery and research waste must be reduced. Trials have been making inconsistent use of healthcare systems data, not least because of an absence of evidence of utility. DUCkS can also help to identify challenges in using healthcare systems data, such as linkage (access and timing) and data quality. We encourage trial teams to incorporate and report DUCkS in trials and funders and data providers to support them.

Taxonomic account and phylogenetic relationships of the species of the Neotropical social wasp genus Chartergus Lepeletier, 1836 (Vespidae: Polistinae: Epiponini).

The Neotropical social wasp genus Chartergus is reviewed and comparative diagnoses, images of type material, and an updated identification key for species are presented. To investigate the phylogenetic relationships within the genus, we used a combined dataset of morphological characters, nest architecture traits, and molecular data. The results revealed the following relationships among the Chartergus species: (C. globiventris + (C. artifex + C. metanotalis)).

Human Nephrogenesis can Persist Beyond 40 Postnatal Days in Preterm Infants.

Introduction: Human nephrogenesis is typically completed by 36 weeks gestation; however, it is impacted by preterm birth. Early studies suggested that nephrogenesis persisted for ≤40 postnatal days in preterm infants. However, the postmenstrual age (PMA) of the preterm infants who survived >40 days was uncertain. In this study, we sought to reexamine postnatal kidney development in preterm infants surviving >40 days. Methods: Human kidney samples were obtained from an institutional biobank. Samples were considered controls if survival was ≤4 days after birth with PMA of 30 to ≤36 weeks. Kidneys from preterm neonates with postnatal survival >40 days and PMA of 30 to ≤36 weeks were compared to controls. We counted glomerular generations, measured nephrogenic zone widths (NZW), and performed immunofluorescence (IF) with SIX1 and RET. We compared kidney weights and quantified the cross-sectional area of proximal (lotus tetragonolobus lectin [LTL], SL22A2), distal (SLC12A3, KCNJ10), and glomerular (nephrin) markers using IF. Results: Seven preterm infants surviving >40 days and 8 controls were analyzed. Four of 7 preterm infants had histologic and molecular evidence of nephrogenesis. Cessation of nephrogenesis in preterm infants occurred 2 weeks earlier than PMA-matched controls with attenuated expression of both SIX1 and RET. We found increased kidney weight-to-body weight ratio, increased distal tubular cross-sectional staining in the superficial nephrons, and distal tubular hypertrophy and hyperplasia in the preterm infant kidneys. Conclusion: Our study supports that nephrogenesis in preterm infants persists longer than previously thought with evidence of early nephron stress, placing importance on the neonatal environment.

Comment on Oberman & Vink: Should we fix or simulate the complete data in simulation studies evaluating missing data methods?

For simulation studies that evaluate methods of handling missing data, we argue that generating partially observed data by fixing the complete data and repeatedly simulating the missingness indicators is a superficially attractive idea but only rarely appropriate to use.

Improving transportability of randomized controlled trial inference using robust prediction methods.

Randomized trials have been the gold standard for assessing causal effects since their introduction by Fisher in the 1920s, since they can eliminate both observed and unobserved confounding. Estimates of causal effects at the population level from randomized controlled trials can still be biased if there are both effect modification and systematic differences between the trial sample and the ultimate population of inference with respect to these modifiers. Recent advances in the survey statistics literature to improve inference in nonprobability samples by using information from probability samples can provide an avenue for improving population causal inference in randomized controlled trials when relevant probability samples of the patient population are available. We review some recent work in "transporting" causal effect estimates from trials to populations, focusing on the setting where there is a "benchmark" or population-representative sample along with the RCT sample. We then propose estimators using either inverse probability weighting (IPWT) or prediction that can accommodate unequal probability of selection in the "benchmark" or population, and use Bayesian additive regression trees for both inverse probability of treatment weighting and prediction estimation that do not require specification of functional form or interaction. We also consider how the assumption of ignorability may be assessed from observed data and propose a sensitivity analysis under the failure of this assumption. We compare our proposed approach with existing methods in simulation and apply these alternative approaches to a study of pulmonary artery catheterization in critically ill patients. We also suggest next steps for future work.

Multiple imputation of missing data under missing at random: including a collider as an auxiliary variable in the imputation model can induce bias.

Epidemiological studies often have missing data, which are commonly handled by multiple imputation (MI). In MI, in addition to those required for the substantive analysis, imputation models often include other variables ("auxiliary variables"). Auxiliary variables that predict the partially observed variables can reduce the standard error (SE) of the MI estimator and, if they also predict the probability that data are missing, reduce bias due to data being missing not at random. However, guidance for choosing auxiliary variables is lacking. We examine the consequences of a poorly chosen auxiliary variable: if it shares a common cause with the partially observed variable and the probability that it is missing (i.e., it is a "collider"), its inclusion can induce bias in the MI estimator and may increase the SE. We quantify, both algebraically and by simulation, the magnitude of bias and SE when either the exposure or outcome is incomplete. When the substantive analysis outcome is partially observed, the bias can be substantial, relative to the magnitude of the exposure coefficient. In settings in which a complete records analysis is valid, the bias is smaller when the exposure is partially observed. However, bias can be larger if the outcome also causes missingness in the exposure. When using MI, it is important to examine, through a combination of data exploration and considering plausible casual diagrams and missingness mechanisms, whether potential auxiliary variables are colliders.

A new approach to evaluating loop inconsistency in network meta-analysis.

In network meta-analysis, studies evaluating multiple treatment comparisons are modeled simultaneously, and estimation is informed by a combination of direct and indirect evidence. Network meta-analysis relies on an assumption of consistency, meaning that direct and indirect evidence should agree for each treatment comparison. Here we propose new local and global tests for inconsistency and demonstrate their application to three example networks. Because inconsistency is a property of a loop of treatments in the network meta-analysis, we locate the local test in a loop. We define a model with one inconsistency parameter that can be interpreted as loop inconsistency. The model builds on the existing ideas of node-splitting and side-splitting in network meta-analysis. To provide a global test for inconsistency, we extend the model across multiple independent loops with one degree of freedom per loop. We develop a new algorithm for identifying independent loops within a network meta-analysis. Our proposed models handle treatments symmetrically, locate inconsistency in loops rather than in nodes or treatment comparisons, and are invariant to choice of reference treatment, making the results less dependent on model parameterization. For testing global inconsistency in network meta-analysis, our global model uses fewer degrees of freedom than the existing design-by-treatment interaction approach and has the potential to increase power. To illustrate our methods, we fit the models to three network meta-analyses varying in size and complexity. Local and global tests for inconsistency are performed and we demonstrate that the global model is invariant to choice of independent loops.

A Catalogue of the Pacific Eumeninae (Hymenoptera: Vespidae).

A catalogue of Eumeninae occurring in Oceania is presented, the first in more than a century.

Multiple imputation approaches for epoch-level accelerometer data in trials.

Clinical trials that investigate physical activity interventions often use accelerometers to measure step count at a very granular level, for example in 5-second epochs. Participants typically wear the accelerometer for a week-long period at baseline, and for one or more week-long follow-up periods after the intervention. The data is aggregated to provide daily or weekly step counts for the primary analysis. Missing data are common as participants may not wear the device as per protocol. Approaches to handling missing data in the literature have defined missingness on the day level using a threshold on daily weartime, which leads to loss of information on the time of day when data are missing. We propose an approach to identifying and classifying missingness at the finer epoch-level and present two approaches to handling missingness using multiple imputation. Firstly, we present a parametric approach which accounts for the number of missing epochs per day. Secondly, we describe a non-parametric approach where missing periods during the day are replaced by donor data from the same person where possible, or data from a different person who is matched on demographic and physical activity-related variables. Our simulation studies show that the non-parametric approach leads to estimates of the effect of treatment that are least biased while maintaining small standard errors. We illustrate the application of these different multiple imputation strategies to the analysis of the 2017 PACE-UP trial. The proposed framework is likely to be applicable to other digital health outcomes and to other wearable devices.

High-concentration buprenorphine exceeds target plasma concentrations for extended periods following subcutaneous administration in American flamingos (Phoenicopterus ruber).

OBJECTIVE: To determine the pharmacokinetic parameters of a high-concentration buprenorphine formulation after a single SC dose in American flamingos (Phoenicopterus ruber). ANIMALS: 6 healthy adult American flamingos (3 males and 3 females). METHODS: A single dose of high-concentration buprenorphine (1.8 mg/kg) was administered SC to all birds. Blood samples were collected at 0.25, 0.5, 1, 2, 4, 8, 12, 24, 48, 72, and 96 hours after drug administration between October 14 and October 18, 2022. Plasma buprenorphine concentrations were determined by liquid chromatography-tandem mass spectrometry and a noncompartmental analysis was used to determine pharmacokinetic parameters. RESULTS: Mean ± SD peak plasma drug concentration (Cmax) was 195.1 ± 187.4 ng/mL, the mean time to peak plasma concentration (Tmax) was 0.32 ± 0.31 hours, the mean area under the concentration-vs-time curve from time 0 to the last measured concentration (AUC0-last) was 881.4 ± 205.4 ng/mL, and mean terminal half-life (t1/2) was 12.6 ± 3.86 hours. Mean plasma buprenorphine concentrations were >1 ng/mL for at least 48 hours after drug administration. No clinically significant adverse effects were observed. CLINICAL RELEVANCE: High-concentration buprenorphine dosed at 1.8 mg/kg SC in American flamingos rapidly exceeded plasma drug concentrations reported to have analgesic effects in other avian species and maintained these levels for extended periods. Sedative effects were similar to those reported for other species. Additional studies are needed to evaluate the clinical efficacy of high-concentration buprenorphine at this dose in American flamingos.

Handling intercurrent events and missing data in non-inferiority trials using the estimand framework: A tuberculosis case study.

INTRODUCTION: The ICH E9 addendum outlining the estimand framework for clinical trials was published in 2019 but provides limited guidance around how to handle intercurrent events for non-inferiority studies. Once an estimand is defined, it is also unclear how to deal with missing values using principled analyses for non-inferiority studies. METHODS: Using a tuberculosis clinical trial as a case study, we propose a primary estimand, and an additional estimand suitable for non-inferiority studies. For estimation, multiple imputation methods that align with the estimands for both primary and sensitivity analysis are proposed. We demonstrate estimation methods using the twofold fully conditional specification multiple imputation algorithm and then extend and use reference-based multiple imputation for a binary outcome to target the relevant estimands, proposing sensitivity analyses under each. We compare the results from using these multiple imputation methods with those from the original study. RESULTS: Consistent with the ICH E9 addendum, estimands can be constructed for a non-inferiority trial which improves on the per-protocol/intention-to-treat-type analysis population previously advocated, involving respectively a hypothetical or treatment policy strategy to handle relevant intercurrent events. Results from using the 'twofold' multiple imputation approach to estimate the primary hypothetical estimand, and using reference-based methods for an additional treatment policy estimand, including sensitivity analyses to handle the missing data, were consistent with the original study's reported per-protocol and intention-to-treat analysis in failing to demonstrate non-inferiority. CONCLUSIONS: Using carefully constructed estimands and appropriate primary and sensitivity estimators, using all the information available, results in a more principled and statistically rigorous approach to analysis. Doing so provides an accurate interpretation of the estimand.

Multiple imputation of missing data under missing at random: compatible imputation models are not sufficient to avoid bias if they are mis-specified.

OBJECTIVES: Epidemiological studies often have missing data, which are commonly handled by multiple imputation (MI). Standard (default) MI procedures use simple linear covariate functions in the imputation model. We examine the bias that may be caused by acceptance of this default option and evaluate methods to identify problematic imputation models, providing practical guidance for researchers. STUDY DESIGN AND SETTING: Using simulation and real data analysis, we investigated how imputation model mis-specification affected MI performance, comparing results with complete records analysis (CRA). We considered scenarios in which imputation model mis-specification occurred because (i) the analysis model was mis-specified or (ii) the relationship between exposure and confounder was mis-specified. RESULTS: Mis-specification of the relationship between outcome and exposure, or between exposure and confounder, can cause biased CRA and MI estimates (in addition to any bias in the full-data estimate due to analysis model mis-specification). MI by predictive mean matching can mitigate model mis-specification. Methods for examining model mis-specification were effective in identifying mis-specified relationships. CONCLUSION: When using MI methods that assume data are MAR, compatibility between the analysis and imputation models is necessary, but not sufficient to avoid bias. We propose a step-by-step procedure for identifying and correcting mis-specification of imputation models.

Revision of the Afrotropical species of the genus Anterhynchium de Saussure (Hymenoptera: Vespidae: Eumeninae).

A taxonomic study on the Afrotropical species in the genus Anterhynchium de Saussure, 1863 is presented. Some subspecies are elevated to specific rank (Anterhynchium argenteopilosellum (Giordani Soika, 1937) stat. nov., A. bugandanum Giordani Soika, 1987 stat. nov., A. cariosum Giordani Soika, 1987 stat. nov., A. denticulatum (Mocsáry, 1903) stat. nov., A. sulphureomaculatum (von Schulthess, 1928) stat. nov.). New synonymies are proposed for Anterhynchium fallax (de Saussure, 1852) (=Rhynchium luctuosum Gerstäcker 1857 syn. nov.), Anterhynchium grandidieri (de Saussure, 1890) (= Epiodynerus grandidieri limbatulus Giordani Soika, 1991 syn. nov.), Anterhynchium grayi (de Saussure, 1855) (= Synagris inermis var. atrata Mocsáry, 1903 syn. nov.; = Rhynchium grayi var. sumptuosum Gribodo, 1895 syn. nov.), Anterhynchium mephisto (Gribodo, 1892) (= Anterhynchium beninum Gusenleitner, 2018 syn. nov.; = Odynerus rufoniger Bequaert, 1918 syn. nov.; = Synagris uncata Tullgren, 1904 syn. nov.); Anterhynchium synagroide (de Saussure, 1852) (=Rhynchium synagroides var. alpha von Schulthess, 1923 syn. nov.; Rhynchium synagroides var. beta von Schulthess, 1923 syn. nov.), Anterhynchium andreanum (de Saussure, 1890) (= Odynerus andreanus discolor Giordani Soika, 1941 syn. nov.); Anterhynchium synagroide gamma (von Schulthess, 1924) is considered as a doubtful synonym of A. argenteopilosellum syn. nov. The nominal subgenus is redefined and divided into the following species-groups: grayi species-group, mephisto species-group, osborni species-group and synagroide species-group. The Malagasy species are transferred from Epiodynerus Giordani Soika to the nominal subgenus but considered as incertae sedis in it. Odynerus natalensis de Saussure, 1855 and Anterhynchium uniforme Gusenleitner, 2012 are transferred to Antodynerus de Saussure, 1855 (Antodynerus natalensis comb. nov. and Antodynerus uniforme comb. nov.), Rhynchium histrionicum Gerstäcker, 1857 is transferred to Euodynerus Dalla Torre, 1904 (Euodynerus (Euodynerus) histrionicus comb. nov.), Rhynchium holomelas André, 1895 is transferred to Pseudagris de Saussure, 1863 (Pseudagris holomelas comb. nov.; = Rhynchium junodianum von Schulthess, 1899 syn. nov.; = Synagris aterrima Maidl, 1914 syn. nov.), Anterhynchium obscurum Gusenleitner, 2007 is transferred to Tricarinodynerus Giordani Soika, 1952 (Tricarinodynerus obscurus comb. nov.). Anterhynchium dahomeyicus Gusenleitner, 2018 is a junior synonym of Aethiopicodynerus punctiventris (Gusenleitner, 2002) syn. nov. Lectotypes for Odynerus andreanus de Saussure, 1890 and Rhynchium sulphureomaculatum von Schulthess, 1928 are designated. A key to the species is provided.

Towards a multi-arm multi-stage platform trial of disease modifying approaches in Parkinson's disease.

An increase in the efficiency of clinical trial conduct has been successfully demonstrated in the oncology field, by the use of multi-arm, multi-stage trials allowing the evaluation of multiple therapeutic candidates simultaneously, and seamless recruitment to phase 3 for those candidates passing an interim signal of efficacy. Replicating this complex innovative trial design in diseases such as Parkinson's disease is appealing, but in addition to the challenges associated with any trial assessing a single potentially disease modifying intervention in Parkinson's disease, a multi-arm platform trial must also specifically consider the heterogeneous nature of the disease, alongside the desire to potentially test multiple treatments with different mechanisms of action. In a multi-arm trial, there is a need to appropriately stratify treatment arms to ensure each are comparable with a shared placebo/standard of care arm; however, in Parkinson's disease there may be a preference to enrich an arm with a subgroup of patients that may be most likely to respond to a specific treatment approach. The solution to this conundrum lies in having clearly defined criteria for inclusion in each treatment arm as well as an analysis plan that takes account of predefined subgroups of interest, alongside evaluating the impact of each treatment on the broader population of Parkinson's disease patients. Beyond this, there must be robust processes of treatment selection, and consensus derived measures to confirm target engagement and interim assessments of efficacy, as well as consideration of the infrastructure needed to support recruitment, and the long-term funding and sustainability of the platform. This has to incorporate the diverse priorities of clinicians, triallists, regulatory authorities and above all the views of people with Parkinson's disease.

Pharmacokinetics of mavacoxib in New Zealand White rabbits (Oryctolagus cuniculus).

OBJECTIVES: To characterize the pharmacokinetics of a single oral dose (6 mg/kg) of mavacoxib in New Zealand White rabbits (Oryctolagus cuniculus) and to characterize any clinicopathologic effects with this medication and dose. ANIMALS: Six healthy, 4-month-old New Zealand White rabbits (3 male, 3 female). PROCEDURES: Before drug administration, clinicopathologic samples were collected for baseline data (CBC, serum biochemical analyses, and urinalysis including urine protein-to-creatinine ratio). All 6 rabbits received a single oral dose (6 mg/kg) of mavacoxib. Clinicopathologic samples were collected at set time intervals to compare with the baseline. Plasma mavacoxib concentrations were determined using liquid chromatography with mass spectrometry, and pharmacokinetic analysis was performed using non-compartmental methods. RESULTS: After a single oral dose, the maximum plasma concentration (Cmax; mean, range) was 854 (713-1040) ng/mL, the time to Cmax (tmax) was 0.36 (0.17-0.50) days, the area under the curve from 0 to the last measured time point (AUC0-last) was 2000 (1765-2307) days*ng/mL, the terminal half-life (t1/2) was 1.63 (1.30-2.26) days, and the terminal rate constant (λz) was 0.42 (0.31-0.53) days. All results for CBCs, serum biochemical analyses, urinalyses, and urine protein-to-creatinine ratios remained within published normal reference intervals. CLINICAL RELEVANCE: This study determined that plasma concentrations reached target levels of 400 ng/mL for 48 hours in 3/6 rabbits at 6 mg/kg PO. In the remaining 3/6 rabbits, the plasma concentrations were 343-389 ng/mL at 48 hours, which is below the target concentration. Further research is needed to make a dosing recommendation, including a pharmacodynamic study and investigating pharmacokinetics at different doses and multiple doses.

Meniscal and Articular Cartilage Predictors of Outcome After Revision ACL Reconstruction: A 6-Year Follow-up Cohort Study.

BACKGROUND: Meniscal and chondral damage is common in the patient undergoing revision anterior cruciate ligament (ACL) reconstruction. PURPOSE: To determine if meniscal and/or articular cartilage pathology at the time of revision ACL surgery significantly influences a patient's outcome at 6-year follow-up. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: Patients undergoing revision ACL reconstruction were prospectively enrolled between 2006 and 2011. Data collection included baseline demographics, surgical technique, pathology, treatment, and scores from 4 validated patient-reported outcome instruments: International Knee Documentation Committee (IKDC), Knee injury and Osteoarthritis Outcome Score (KOOS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and Marx Activity Rating Scale. Patients were followed up at 6 years and asked to complete the identical set of outcome instruments. Regression analysis assessed the meniscal and articular cartilage pathology risk factors for clinical outcomes 6 years after revision ACL reconstruction. RESULTS: An overall 1234 patients were enrolled (716 males, 58%; median age, 26 years). Surgeons reported the pathology at the time of revision surgery in the medial meniscus (45%), lateral meniscus (36%), medial femoral condyle (43%), lateral femoral condyle (29%), medial tibial plateau (11%), lateral tibial plateau (17%), patella (30%), and trochlea (21%). Six-year follow-up was obtained on 79% of the sample (980/1234). Meniscal pathology and articular cartilage pathology (medial femoral condyle, lateral femoral condyle, lateral tibial plateau, trochlea, and patella) were significant drivers of poorer patient-reported outcomes at 6 years (IKDC, KOOS, WOMAC, and Marx). The most consistent factors driving outcomes were having a medial meniscal excision (either before or at the time of revision surgery) and patellofemoral articular cartilage pathology. Six-year Marx activity levels were negatively affected by having either a repair/excision of the medial meniscus (odds ratio range, 1.45-1.72; P≤ .04) or grade 3-4 patellar chondrosis (odds ratio, 1.72; P = .04). Meniscal pathology occurring before the index revision surgery negatively affected scores on all KOOS subscales except for sports/recreation (P < .05). Articular cartilage pathology significantly impaired all KOOS subscale scores (P < .05). Lower baseline outcome scores, higher body mass index, being a smoker, and incurring subsequent surgery all significantly increased the odds of reporting poorer clinical outcomes at 6 years. CONCLUSION: Meniscal and chondral pathology at the time of revision ACL reconstruction has continued significant detrimental effects on patient-reported outcomes at 6 years after revision surgery.