Quantification of follow-up time in oncology clinical trials with a time-to-event endpoint: Asking the right questions.

For the analysis of a time-to-event endpoint in a single-arm or randomized clinical trial it is generally perceived that interpretation of a given estimate of the survival function, or the comparison between two groups, hinges on some quantification of the amount of follow-up. Typically, a median of some loosely defined quantity is reported. However, whatever median is reported, is typically not answering the question(s) trialists actually have in terms of follow-up quantification. In this paper, inspired by the estimand framework, we formulate a comprehensive list of relevant scientific questions that trialists have when reporting time-to-event data. We illustrate how these questions should be answered, and that reference to an unclearly defined follow-up quantity is not needed at all. In drug development, key decisions are made based on randomized controlled trials, and we therefore also discuss relevant scientific questions not only when looking at a time-to-event endpoint in one group, but also for comparisons. We find that different thinking about some of the relevant scientific questions around follow-up is required depending on whether a proportional hazards assumption can be made or other patterns of survival functions are anticipated, for example, delayed separation, crossing survival functions, or the potential for cure. We conclude the paper with practical recommendations.

Conditional power and friends: The why and how of (un)planned, unblinded sample size recalculations in confirmatory trials.

Adapting the final sample size of a trial to the evidence accruing during the trial is a natural way to address planning uncertainty. Since the sample size is usually determined by an argument based on the power of the trial, an interim analysis raises the question of how the final sample size should be determined conditional on the accrued information. To this end, we first review and compare common approaches to estimating conditional power, which is often used in heuristic sample size recalculation rules. We then discuss the connection of heuristic sample size recalculation and optimal two-stage designs, demonstrating that the latter is the superior approach in a fully preplanned setting. Hence, unplanned design adaptations should only be conducted as reaction to trial-external new evidence, operational needs to violate the originally chosen design, or post hoc changes in the optimality criterion but not as a reaction to trial-internal data. We are able to show that commonly discussed sample size recalculation rules lead to paradoxical adaptations where an initially planned optimal design is not invariant under the adaptation rule even if the planning assumptions do not change. Finally, we propose two alternative ways of reacting to newly emerging trial-external evidence in ways that are consistent with the originally planned design to avoid such inconsistencies.

Estimands for overall survival in clinical trials with treatment switching in oncology.

An addendum of the ICH E9 guideline on Statistical Principles for Clinical Trials was released in November 2019 introducing the estimand framework. This new framework aims to align trial objectives and statistical analyses by requiring a precise definition of the inferential quantity of interest, that is, the estimand. This definition explicitly accounts for intercurrent events, such as switching to new anticancer therapies for the analysis of overall survival (OS), the gold standard in oncology. Traditionally, OS in confirmatory studies is analyzed using the intention-to-treat (ITT) approach comparing treatment groups as they were initially randomized regardless of whether treatment switching occurred and regardless of any subsequent therapy (treatment-policy strategy). Regulatory authorities and other stakeholders often consider ITT results as most relevant. However, the respective estimand only yields a clinically meaningful comparison of two treatment arms if subsequent therapies are already approved and reflect clinical practice. We illustrate different scenarios where subsequent therapies are not yet approved drugs and thus do not reflect clinical practice. In such situations the hypothetical strategy could be more meaningful from patient's and prescriber's perspective. The cross-industry Oncology Estimand Working Group (www.oncoestimand.org) was initiated to foster a common understanding and consistent implementation of the estimand framework in oncology clinical trials. This paper summarizes the group's recommendations for appropriate estimands in the presence of treatment switching, one of the key intercurrent events in oncology clinical trials. We also discuss how different choices of estimands may impact study design, data collection, trial conduct, analysis, and interpretation.

Estimands in hematologic oncology trials.

The estimand framework included in the addendum to the ICH E9 guideline facilitates discussions to ensure alignment between the key question of interest, the analysis, and interpretation. Therapeutic knowledge and drug mechanism play a crucial role in determining the strategy and defining the estimand for clinical trial designs. Clinical trials in patients with hematological malignancies often present unique challenges for trial design due to complexity of treatment options and existence of potential curative but highly risky procedures, for example, stem cell transplant or treatment sequence across different phases (induction, consolidation, maintenance). Here, we illustrate how to apply the estimand framework in hematological clinical trials and how the estimand framework can address potential difficulties in trial result interpretation. This paper is a result of a cross-industry collaboration to connect the International Conference on Harmonisation (ICH) E9 addendum concepts to applications. Three randomized phase 3 trials will be used to consider common challenges including intercurrent events in hematologic oncology trials to illustrate different scientific questions and the consequences of the estimand choice for trial design, data collection, analysis, and interpretation. Template language for describing estimand in both study protocols and statistical analysis plans is suggested for statisticians' reference.

Principal stratum strategy: Potential role in drug development.

A randomized trial allows estimation of the causal effect of an intervention compared to a control in the overall population and in subpopulations defined by baseline characteristics. Often, however, clinical questions also arise regarding the treatment effect in subpopulations of patients, which would experience clinical or disease related events post-randomization. Events that occur after treatment initiation and potentially affect the interpretation or the existence of the measurements are called intercurrent events in the ICH E9(R1) guideline. If the intercurrent event is a consequence of treatment, randomization alone is no longer sufficient to meaningfully estimate the treatment effect. Analyses comparing the subgroups of patients without the intercurrent events for intervention and control will not estimate a causal effect. This is well known, but post-hoc analyses of this kind are commonly performed in drug development. An alternative approach is the principal stratum strategy, which classifies subjects according to their potential occurrence of an intercurrent event on both study arms. We illustrate with examples that questions formulated through principal strata occur naturally in drug development and argue that approaching these questions with the ICH E9(R1) estimand framework has the potential to lead to more transparent assumptions as well as more adequate analyses and conclusions. In addition, we provide an overview of assumptions required for estimation of effects in principal strata. Most of these assumptions are unverifiable and should hence be based on solid scientific understanding. Sensitivity analyses are needed to assess robustness of conclusions.

Survival analysis for AdVerse events with VarYing follow-up times (SAVVY): Rationale and statistical concept of a meta-analytic study.

The assessment of safety is an important aspect of the evaluation of new therapies in clinical trials, with analyses of adverse events being an essential part of this. Standard methods for the analysis of adverse events such as the incidence proportion, that is the number of patients with a specific adverse event out of all patients in the treatment groups, do not account for both varying follow-up times and competing risks. Alternative approaches such as the Aalen-Johansen estimator of the cumulative incidence function have been suggested. Theoretical arguments and numerical evaluations support the application of these more advanced methodology, but as yet there is to our knowledge only insufficient empirical evidence whether these methods would lead to different conclusions in safety evaluations. The Survival analysis for AdVerse events with VarYing follow-up times (SAVVY) project strives to close this gap in evidence by conducting a meta-analytical study to assess the impact of the methodology on the conclusion of the safety assessment empirically. Here we present the rationale and statistical concept of the empirical study conducted as part of the SAVVY project. The statistical methods are presented in unified notation, and examples of their implementation in R and SAS are provided.

Obinutuzumab for the First-Line Treatment of Follicular Lymphoma.

BACKGROUND: Rituximab-based immunochemotherapy has improved outcomes in patients with follicular lymphoma. Obinutuzumab is a glycoengineered type II anti-CD20 monoclonal antibody. We compared rituximab-based chemotherapy with obinutuzumab-based chemotherapy in patients with previously untreated advanced-stage follicular lymphoma. METHODS: We randomly assigned patients to undergo induction treatment with obinutuzumab-based chemotherapy or rituximab-based chemotherapy. Patients with a response received maintenance treatment for up to 2 years with the same antibody that they had received in induction. The primary end point was investigator-assessed progression-free survival. RESULTS: A total of 1202 patients with follicular lymphoma underwent randomization (601 patients in each group). After a median follow-up of 34.5 months (range, 0 to 54.5), a planned interim analysis showed that obinutuzumab-based chemotherapy resulted in a significantly lower risk of progression, relapse, or death than rituximab-based chemotherapy (estimated 3-year rate of progression-free survival, 80.0% vs. 73.3%; hazard ratio for progression, relapse, or death, 0.66; 95% confidence interval [CI], 0.51 to 0.85; P=0.001). Similar results were seen with regard to independently reviewed progression-free survival and other time-to-event end points. Response rates were similar in the two groups (88.5% in the obinutuzumab group and 86.9% in the rituximab group). Adverse events of grade 3 to 5 were more frequent in the obinutuzumab group than in the rituximab group (74.6% vs. 67.8%), as were serious adverse events (46.1% vs. 39.9%). The rates of adverse events resulting in death were similar in the two groups (4.0% in the obinutuzumab group and 3.4% in the rituximab group). The most common adverse events were infusion-related events that were considered by the investigators to be largely due to obinutuzumab in 353 of 595 patients (59.3%; 95% CI, 55.3 to 63.2) and to rituximab in 292 of 597 patients (48.9%; 95% CI, 44.9 to 52.9; P<0.001). Nausea and neutropenia were common. A total of 35 patients (5.8%) in the obinutuzumab group and 46 (7.7%) in the rituximab group died. CONCLUSIONS: Obinutuzumab-based immunochemotherapy and maintenance therapy resulted in longer progression-free survival than rituximab-based therapy. High-grade adverse events were more common with obinutuzumab-based chemotherapy. (Funded by F. Hoffmann-La Roche; GALLIUM ClinicalTrials.gov number, NCT01332968 .).

MRI of the sacroiliac joints in athletes: recognition of non-specific bone marrow oedema by semi-axial added to standard semi-coronal scans.

OBJECTIVE: Assessment of combined semi-axial and semi-coronal SI joint MRI in two cohorts of young athletes to explore frequency and topography of non-specific bone marrow oedema (BMO), its association with four constitutional SI joint features, and potential restriction of false-positive assignments of Assessment of SpondyloArthritis International Society-defined sacroiliitis on standard semi-coronal scans alone. METHODS: Combined semi-axial and semi-coronal SI joint MRI scans of 20 recreational runners before/after running and 22 elite ice-hockey players were evaluated by three blinded readers for BMO and its association with four constitutional SI joint features: vascular partial volume effect, deep iliac ligament insertion, fluid-filled bone cyst and lumbosacral transitional anomaly. Scans of TNF-treated spondyloarthritis patients served to mask readers. We analysed distribution and topography of BMO and SI joint features across eight anatomical SI joint regions (upper/lower ilium/sacrum, subdivided in anterior/posterior slices) descriptively, as concordantly recorded by ⩾2/3 readers on both MRI planes. BMO confirmed on both scans was compared with previous evaluation of semi-coronal MRI alone, which met the Assessment of SpondyloArthritis International Society definition for active sacroiliitis. RESULTS: Perpendicular semi-axial and semi-coronal MRI scans confirmed BMO in the SI joint of every fourth young athlete, preferentially in the anterior upper sacrum. BMO associated with four constitutional SI joint features was observed in 20-36% of athletes, clustering in the posterior lower ilium. The proportion of Assessment of SpondyloArthritis International Society-positive sacroiliitis recorded on the semi-coronal plane alone decreased by 33-56% upon amending semi-axial scans. CONCLUSION: Semi-axial combined with standard semi-coronal scans in MRI protocols for sacroiliitis facilitated recognition of non-specific BMO, which clustered in posterior lower ilium/anterior upper sacrum.

Integrating phase 2 into phase 3 based on an intermediate endpoint while accounting for a cure proportion-With an application to the design of a clinical trial in acute myeloid leukemia.

For a trial with primary endpoint overall survival for a molecule with curative potential, statistical methods that rely on the proportional hazards assumption may underestimate the power and the time to final analysis. We show how a cure proportion model can be used to get the necessary number of events and appropriate timing via simulation. If phase 1 results for the new drug are exceptional and/or the medical need in the target population is high, a phase 3 trial might be initiated after phase 1. Building in a futility interim analysis into such a pivotal trial may mitigate the uncertainty of moving directly to phase 3. However, if cure is possible, overall survival might not be mature enough at the interim to support a futility decision. We propose to base this decision on an intermediate endpoint that is sufficiently associated with survival. Planning for such an interim can be interpreted as making a randomized phase 2 trial a part of the pivotal trial: If stopped at the interim, the trial data would be analyzed, and a decision on a subsequent phase 3 trial would be made. If the trial continues at the interim, then the phase 3 trial is already underway. To select a futility boundary, a mechanistic simulation model that connects the intermediate endpoint and survival is proposed. We illustrate how this approach was used to design a pivotal randomized trial in acute myeloid leukemia and discuss historical data that informed the simulation model and operational challenges when implementing it.

A multistate model for early decision-making in oncology.

The development of oncology drugs progresses through multiple phases, where after each phase, a decision is made about whether to move a molecule forward. Early phase efficacy decisions are often made on the basis of single-arm studies based on a set of rules to define whether the tumor improves ("responds"), remains stable, or progresses (response evaluation criteria in solid tumors [RECIST]). These decision rules are implicitly assuming some form of surrogacy between tumor response and long-term endpoints like progression-free survival (PFS) or overall survival (OS). With the emergence of new therapies, for which the link between RECIST tumor response and long-term endpoints is either not accessible yet, or the link is weaker than with classical chemotherapies, tumor response-based rules may not be optimal. In this paper, we explore the use of a multistate model for decision-making based on single-arm early phase trials. The multistate model allows to account for more information than the simple RECIST response status, namely, the time to get to response, the duration of response, the PFS time, and time to death. We propose to base the decision on efficacy on the OS hazard ratio (HR) comparing historical control to data from the experimental treatment, with the latter predicted from a multistate model based on early phase data with limited survival follow-up. Using two case studies, we illustrate feasibility of the estimation of such an OS HR. We argue that, in the presence of limited follow-up and small sample size, and making realistic assumptions within the multistate model, the OS prediction is acceptable and may lead to better early decisions within the development of a drug.

Joint modeling of progression-free and overall survival and computation of correlation measures.

In this paper, we derive the joint distribution of progression-free and overall survival as a function of transition probabilities in a multistate model. No assumptions on copulae or latent event times are needed and the model is allowed to be non-Markov. From the joint distribution, statistics of interest can then be computed. As an example, we provide closed formulas and statistical inference for Pearson's correlation coefficient between progression-free and overall survival in a parametric framework. The example is inspired by recent approaches to quantify the dependence between progression-free survival, a common primary outcome in Phase 3 trials in oncology and overall survival. We complement these approaches by providing methods of statistical inference while at the same time working within a much more parsimonious modeling framework. Our approach is completely general and can be applied to other measures of dependence. We also discuss extensions to nonparametric inference. Our analytical results are illustrated using a large randomized clinical trial in breast cancer.

Treatment effect quantification for time-to-event endpoints-Estimands, analysis strategies, and beyond.

A draft addendum to ICH E9 has been released for public consultation in August 2017. The addendum focuses on two topics particularly relevant for randomized confirmatory clinical trials: estimands and sensitivity analyses. The need to amend ICH E9 grew out of the realization of a lack of alignment between the objectives of a clinical trial stated in the protocol and the accompanying quantification of the "treatment effect" reported in a regulatory submission. We embed time-to-event endpoints in the estimand framework and discuss how the four estimand attributes described in the addendum apply to time-to-event endpoints. We point out that if the proportional hazards assumption is not met, the estimand targeted by the most prevalent methods used to analyze time-to-event endpoints, logrank test, and Cox regression depends on the censoring distribution. We discuss for a large randomized clinical trial how the analyses for the primary and secondary endpoints as well as the sensitivity analyses actually performed in the trial can be seen in the context of the addendum. To the best of our knowledge, this is the first attempt to do so for a trial with a time-to-event endpoint. Questions that remain open with the addendum for time-to-event endpoints and beyond are formulated, and recommendations for planning of future trials are given. We hope that this will provide a contribution to developing a common framework based on the final version of the addendum that can be applied to design, protocols, statistical analysis plans, and clinical study reports in the future.

Sequentially updating the likelihood of success of a Phase 3 pivotal time-to-event trial based on interim analyses or external information.

When performing a pivotal clinical trial, it may be of interest to assess the probability of success (PoS) of that trial. Initially evaluated when the trial is designed, PoS can be updated as the trial progresses and new information about the drug effect becomes available. Such information can be external to the trial, such as results from trials conducted in parallel, or internal, such as continuing after an interim analysis. We develop a framework to update PoS based on such internal and external information for a time-to-event endpoint and illustrate it using a realistic development program for a new molecule.

Bayesian predictive power: choice of prior and some recommendations for its use as probability of success in drug development.

Bayesian predictive power, the expectation of the power function with respect to a prior distribution for the true underlying effect size, is routinely used in drug development to quantify the probability of success of a clinical trial. Choosing the prior is crucial for the properties and interpretability of Bayesian predictive power. We review recommendations on the choice of prior for Bayesian predictive power and explore its features as a function of the prior. The density of power values induced by a given prior is derived analytically and its shape characterized. We find that for a typical clinical trial scenario, this density has a u-shape very similar, but not equal, to a ß-distribution. Alternative priors are discussed, and practical recommendations to assess the sensitivity of Bayesian predictive power to its input parameters are provided. Copyright © 2016 John Wiley & Sons, Ltd.

Comparison of design strategies for a three-arm clinical trial with time-to-event endpoint: Power, time-to-analysis, and operational aspects.

To optimize resources, randomized clinical trials with multiple arms can be an attractive option to simultaneously test various treatment regimens in pharmaceutical drug development. The motivation for this work was the successful conduct and positive final outcome of a three-arm randomized clinical trial primarily assessing whether obinutuzumab plus chlorambucil in patients with chronic lympocytic lymphoma and coexisting conditions is superior to chlorambucil alone based on a time-to-event endpoint. The inference strategy of this trial was based on a closed testing procedure. We compare this strategy to three potential alternatives to run a three-arm clinical trial with a time-to-event endpoint. The primary goal is to quantify the differences between these strategies in terms of the time it takes until the first analysis and thus potential approval of a new drug, number of required events, and power. Operational aspects of implementing the various strategies are discussed. In conclusion, using a closed testing procedure results in the shortest time to the first analysis with a minimal loss in power. Therefore, closed testing procedures should be part of the statistician's standard clinical trials toolbox when planning multiarm clinical trials.

Does spinal MRI add incremental diagnostic value to MRI of the sacroiliac joints alone in patients with non-radiographic axial spondyloarthritis?

OBJECTIVE: To assess the incremental diagnostic value of spine MRI evaluated separately from and combined with sacroiliac joint (SIJ) MRI in non-radiographic axial spondyloarthritis (nr-axSpA) compared with SIJ MRI alone. METHODS: The study sample comprised two independent cohorts A/B of 130 consecutive patients aged ≤50 years with back pain, newly referred to two university clinics, and 20 healthy controls. Patients were classified according to clinical examination and pelvic radiographs as having nr-axSpA (n=50), ankylosing spondylitis (n=33), or non-specific back pain (n=47). Four readers assessed SIJ and spine MRI separately 6 months apart, and 1-12 months later both scans simultaneously using standardised modules. Readers recorded presence/absence of SpA and their level of confidence in this conclusion on a 0-10 scale (0=definitely not; 10=definite). We analysed differences between SIJ MRI versus spine MRI alone, and SIJ MRI alone versus combined MRI, descriptively by the number/percentage of subjects according to the mean of four readers. RESULTS: In cohorts A/B, 15.8%/24.2% of patients with nr-axSpA having a negative SIJ MRI were reclassified as being positive for SpA by global evaluation of combined scans. However, 26.8%/11.4% of non-specific back pain controls and 17.5% of healthy volunteers with a negative SIJ MRI were falsely reclassified as having SpA by combined MRI. Low confidence in a diagnosis of SpA by SIJ MRI increased to high confidence by combined MRI in 6.6%/7.3% of patients with nr-axSpA. CONCLUSIONS: Combined spine and SIJ MRI added little incremental value compared with SIJ MRI alone for diagnosing patients with nr-axSpA and enhancing confidence in this diagnosis.

Candidate lesion-based criteria for defining a positive sacroiliac joint MRI in two cohorts of patients with axial spondyloarthritis.

OBJECTIVE: To determine candidate lesion-based criteria for a positive sacroiliac joint (SIJ) MRI based on bone marrow oedema (BMO) and/or erosion in non-radiographic axial spondyloarthritis (nr-axSpA); to compare the performance of lesion-based criteria with global evaluation by expert readers. METHODS: Two independent cohorts A/B of 69/88 consecutive patients with back pain aged ≤50 years, with median symptom duration 1.3/10.0 years, were referred for suspected SpA (A) or acute anterior uveitis plus back pain (B). Patients were classified according to rheumatologist expert opinion based on clinical examination, pelvic radiography and laboratory values as having nr-axSpA (n=51), ankylosing spondylitis (n=34) or non-specific back pain (n=72). Four blinded readers assessed SIJ MRI, recording the presence/absence of SpA by concomitant global evaluation of T1-weighted spin echo (T1SE) and short τ inversion recovery (STIR) scans and, thereafter, whether BMO and/or erosion were present/absent in each SIJ quadrant of each MRI slice. We derived candidate lesion-based criteria based on the number of SIJ quadrants with BMO and/or erosion and calculated mean sensitivity and specificity for SpA. RESULTS: For both cohorts A/B, global assessment showed high specificity (0.95/0.83) compared with the Assessment in SpondyloArthritis international Society (ASAS) definition (0.76/0.74). BMO ≥3 (0.89/0.84) or ≥4 (0.92/0.87) showed comparably high specificity to global assessment. Erosion ≥2 and/or BMO ≥3 or ≥4 were associated with comparably high sensitivity to global assessment without affecting specificity. These combined criteria showed both higher sensitivity and specificity than the ASAS definition. CONCLUSIONS: Lesion-based criteria for a positive SIJ MRI based on both BMO and/or erosion performed best for classification of axial SpA, reflecting the contextual information provided by T1SE and STIR sequences.

Intracoronary injection of bone marrow-derived mononuclear cells early or late after acute myocardial infarction: effects on global left ventricular function.

BACKGROUND: Intracoronary administration of autologous bone marrow-derived mononuclear cells (BM-MNC) may improve remodeling of the left ventricle (LV) after acute myocardial infarction. The optimal time point of administration of BM-MNC is still uncertain and has rarely been addressed prospectively in randomized clinical trials. METHODS AND RESULTS: In a multicenter study, we randomized 200 patients with large, successfully reperfused ST-segment elevation myocardial infarction in a 1:1:1 pattern into an open-labeled control and 2 BM-MNC treatment groups. In the BM-MNC groups, cells were administered either early (i.e., 5 to 7 days) or late (i.e., 3 to 4 weeks) after acute myocardial infarction. Cardiac magnetic resonance imaging was performed at baseline and after 4 months. The primary end point was the change from baseline to 4 months in global LV ejection fraction between the 2 treatment groups and the control group. The absolute change in LV ejection fraction from baseline to 4 months was -0.4±8.8% (mean±SD; P=0.74 versus baseline) in the control group, 1.8±8.4% (P=0.12 versus baseline) in the early group, and 0.8±7.6% (P=0.45 versus baseline) in the late group. The treatment effect of BM-MNC as estimated by ANCOVA was 1.25 (95% confidence interval, -1.83 to 4.32; P=0.42) for the early therapy group and 0.55 (95% confidence interval, -2.61 to 3.71; P=0.73) for the late therapy group. CONCLUSIONS: Among patients with ST-segment elevation myocardial infarction and LV dysfunction after successful reperfusion, intracoronary infusion of BM-MNC at either 5 to 7 days or 3 to 4 weeks after acute myocardial infarction did not improve LV function at 4-month follow-up. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00355186.

Tumor necrosis factor α inhibition in radiographic and nonradiographic axial spondyloarthritis: results from a large observational cohort.

OBJECTIVE: To evaluate the baseline characteristics of patients with radiographic axial spondyloarthritis (SpA; ankylosing spondylitis [AS]) and patients with nonradiographic axial SpA, to investigate determinants of anti-tumor necrosis factor (anti-TNF) agent prescription on the background of a nonrestrictive reimbursement policy, and to assess the response to TNF inhibition. METHODS: We compared the characteristics of radiographic axial SpA and nonradiographic axial SpA in 1,070 patients from the Swiss Clinical Quality Management (SCQM) Cohort who fulfilled the Assessment of SpondyloArthritis international Society (ASAS) classification criteria for axial SpA. By taking advantage of the situation that patients who are eligible for anti-TNF treatment are preferentially enrolled in the SCQM Cohort for patients with AS/axial SpA, we explored parameters leading to the initiation of anti-TNF treatment in single and multiple regression models and assessed treatment responses. RESULTS: We confirmed a similar burden of disease (as determined by self-reported disease activity, impaired function, and quality of life) in patients with nonradiographic axial SpA (n = 232) and those with radiographic axial SpA (n = 838). Patients with radiographic axial SpA had higher median levels of acute-phase reactants and higher median AS Disease Activity Scores (ASDAS; 3.2 versus 3.0). Anti-TNF treatment was initiated in 363 patients with radiographic axial SpA and 102 patients with nonradiographic axial SpA, preferentially in those with sacroiliitis on magnetic resonance imaging, peripheral arthritis, a higher C-reactive protein (CRP) level, a higher ASDAS, and a higher Bath Ankylosing Spondylitis Disease Activity Index level. The ASAS criteria for 40% improvement responses at 1 year were higher in patients with radiographic axial SpA compared with those with nonradiographic axial SpA (48.1% versus 29.6%; odds ratio [OR] 2.2, 95% confidence interval [95% CI] 1.12-4.46, P = 0.02). The difference was smaller in the subgroups of patients with elevated baseline CRP levels (51.6% in patients with radiographic axial SpA versus 38.5% in those with nonradiographic axial SpA; OR 1.7, 95% CI 0.68-4.48, P = 0.29). CONCLUSION: The indications for treatment with anti-TNF agents were comparable for patients with radiographic axial SpA and those with nonradiographic axial SpA. With the exception of patients with elevated CRP levels at baseline, higher rates of response to TNF inhibition were achieved in the group of patients with radiographic axial SpA than in the group with nonradiographic axial SpA.

The Paediatric Palliative Screening Scale: Further validity testing.

BACKGROUND: Paediatric palliative care is still often introduced late in the illness trajectory of children with life-limiting diseases. Translating palliative care into practice continues to be a challenge. AIM: To validate the Paediatric Palliative Screening Scale further by defining attributes that predict the need for palliative care in children between 1 and 18 years. DESIGN: Proportional-odds logistic regression analysis was performed to investigate the relationship between the attributes of the Paediatric Palliative Screening Scale and the experts' assessment of case vignettes with various combinations of different attribute characteristics. Estimates from regression analysis were transformed to empirical weightings of the Paediatric Palliative Screening Scale attribute characteristics. SETTING/PARTICIPANTS: Online questionnaires with case vignettes were sent to 33 paediatric palliative care experts from Europe, the United States, Canada, Australia and New Zealand. RESULTS: The highest weightings among the five previously defined attributes were estimated life expectancy <12 months (40% of maximum score) and preferences of the child/parents received (24%). Trajectory of disease and impact on daily activities of the child, expected outcome of treatment directed at the disease and burden of treatment, and symptom or problem burden were weighted less. CONCLUSIONS: According to this second step of psychometric testing of the Paediatric Palliative Screening Scale, the strongest and most urgent necessity indicators for a palliative care approach are life expectancy and child/family preferences. These results are somewhat discrepant with results from the previous validation of the instrument as well as previous research findings.