22 research outputs found
Performance of binary prediction models in high-correlation low-dimensional settings:a comparison of methods
BACKGROUND: Clinical prediction models are developed widely across medical disciplines. When predictors in such models are highly collinear, unexpected or spurious predictor-outcome associations may occur, thereby potentially reducing face-validity of the prediction model. Collinearity can be dealt with by exclusion of collinear predictors, but when there is no a priori motivation (besides collinearity) to include or exclude specific predictors, such an approach is arbitrary and possibly inappropriate. METHODS: We compare different methods to address collinearity, including shrinkage, dimensionality reduction, and constrained optimization. The effectiveness of these methods is illustrated via simulations. RESULTS: In the conducted simulations, no effect of collinearity was observed on predictive outcomes (AUC, R(2), Intercept, Slope) across methods. However, a negative effect of collinearity on the stability of predictor selection was found, affecting all compared methods, but in particular methods that perform strong predictor selection (e.g., Lasso). Methods for which the included set of predictors remained most stable under increased collinearity were Ridge, PCLR, LAELR, and Dropout. CONCLUSIONS: Based on the results, we would recommend refraining from data-driven predictor selection approaches in the presence of high collinearity, because of the increased instability of predictor selection, even in relatively high events-per-variable settings. The selection of certain predictors over others may disproportionally give the impression that included predictors have a stronger association with the outcome than excluded predictors. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s41512-021-00115-5
Assessing patient-reported outcomes (PROs) and patient-related outcomes in randomized cancer clinical trials for older adults: Results of DATECAN-ELDERLY initiative
As older adults with cancer are underrepresented in randomized clinical trials (RCT), there is limited evidence on which to rely for treatment decisions for this population. Commonly used RCT endpoints for the assessment of treatment efficacy are more often tumor-centered (e.g., progression-free survival). These endpoints may not be as relevant for the older patients who present more often with comorbidities, non–cancer-related deaths, and treatment toxicity. Moreover, their expectation and preferences are likely to differ from younger adults. The DATECAN-ELDERLY initiative combines a broad expertise, in geriatric oncology and clinical research, with interest in cancer RCT that include older patients with cancer. In order to guide researchers and clinicians coordinating cancer RCT involving older patients with cancer, the experts reviewed the literature on relevant domains to assess using patient-reported outcomes (PRO) and patient-related outcomes, as well as available tools related to these domains. Domains considered relevant by the panel of experts when assessing treatment efficacy in RCT for older patients with cancer included functional autonomy, cognition, depression and nutrition. These were based on published guidelines from international societies and from regulatory authorities as well as minimum datasets recommended to collect in RCT including older adults with cancer. In addition, health-related quality of life, patients' symptoms, and satisfaction were also considered by the panel. With regards to tools for the assessment of these domains, we highlighted that each tool has its own strengths and limitations, and very few had been validated in older adults with cancer. Further studies are thus needed to validate these tools in this specific population and define the minimum clinically important difference to use when developing RCTs in this population. The selection of the most relevant tool should thus be guided by the RCT research question, together with the specific properties of the tool
Testing the proportional odds assumption in multiply imputed ordinal longitudinal data
A popular choice when analyzing ordinal data is to consider the cumulative proportional odds model to relate the marginal probabilities of the ordinal outcome to a set of covariates. However, application of this model relies on the condition of identical cumulative odds ratios across the cut-offs of the ordinal outcome; the well-known proportional odds assumption. This paper focuses on the assessment of this assumption while accounting for repeated and missing data. In this respect, we develop a statistical method built on multiple imputation (MI) based on generalized estimating equations that allows to test the proportionality assumption under the missing at random setting. The performance of the proposed method is evaluated for two MI algorithms for incomplete longitudinal ordinal data. The impact of both MI methods is compared with respect to the type I error rate and the power for situations covering various numbers of categories of the ordinal outcome, sample sizes, rates of missingness, well-balanced and skewed data. The comparison of both MI methods with the complete-case analysis is also provided.We illustrate the use of the proposed methods on a quality of life data from a cancer clinical trial
Prophylactic Cranial Irradiation in Extensive Disease Small-Cell Lung Cancer:Short-Term Health-Related Quality of Life and Patient Reported Symptoms-Results of an International Phase III Randomized Controlled Trial by the EORTC Radiation Oncology and Lung Cancer Groups
EORTC liver metastases intergroup randomized phase III study 40983: Long-term survival results.
Lapatinib with ECF/X in the first-line treatment of metastatic gastric cancer according to HER2neu and EGFR status: a randomized placebo-controlled phase II study (EORTC 40071)
PURPOSE: HER2-targeted therapy with trastuzumab and (CF/X) prolonged overall survival (OS) in metastatic HER2neu+ gastric carcinoma (GC). Lapatinib inhibits both EGFR and HER2neu. We investigated the efficacy and safety of lapatinib with epirubicin (E) + CF/X in GC according to HER2neu and EGFR status. METHODS: Tumors from chemotherapy-naïve patients were screened centrally by fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC). Patients with EGFR and/or HER2neu expression or amplification were allocated to three strata based on EGFR/HER2neu status and were randomized to lapatinib (arm A) or placebo (arm B), with 6 cycles of ECF or ECX (investigator-selected). The primary endpoint was progression-free survival (PFS) in stratum 3. RESULTS: 29 of 72 screened patients were randomized to strata 1 (HER2neu+: by FISH and IHC, n = 6), 2 (HER2neu-: by FISH/+ by IHC, n = 5) and 3 (HER2neu-/EGFR+, n = 18), of which 28 patients were eligible (14 per arm). Enrollment was curtailed after announcement of the negative LOGiC trial results. Median PFS was 8.0 versus 5.9 months (HR = 0.86, 95% CI 0.37-1.99) in the per protocol population, and 8.0 versus 6.3 months (HR = 0.85, 95% CI 0.30-2.46) for stratum 3, in the lapatinib versus placebo arm respectively. Median OS was 13.8 versus 10.1 months, respectively (HR = 0.90, 95% CI 0.35-2.27). There were no safety concerns. CONCLUSIONS: Central EGFR and HER2neu stratification by IHC and FISH can be used for further pan-HER strategies. Lapatinib with ECF/X was well tolerated, but did not show clear activity in patients with metastatic GC.status: publishe
Radiofrequency ablation (RFA) combined with chemotherapy for unresectable colorectal liver metastases (CRC LM): Long-term survival results of a randomized phase II study of the EORTC-NCRI CCSG-ALM Intergroup 40004 (CLOCC).
Local treatment of unresectable colorectal liver metastases : results of a randomized phase II trial
Background: Tumor ablation is often employed for unresectable colorectal liver metastases. However, no survival benefit has ever been demonstrated in prospective randomized studies. Here, we investigate the long-term benefits of such an aggressive approach.
Methods: In this randomized phase II trial, 119 patients with unresectable colorectal liver metastases (n 38%) was met. We now report on long-term OS results. All statistical tests were two-sided. The analyses were according to intention to treat.
Results: At a median follow up of 9.7 years, 92 of 119 (77.3%) patients had died: 39 of 60 (65.0%) in the combined modality arm and 53 of 59 (89.8%) in the systemic treatment arm. Almost all patients died of progressive disease (35 patients in the combined modality arm, 49 patients in the systemic treatment arm). There was a statistically significant difference in OS in favor of the combined modality arm (hazard ratio [HR] = 0.58, 95% confidence interval [CI] = 0.38 to 0.88, P = .01). Three-, five-, and eight-year OS were 56.9% (95% CI = 43.3% to 68.5%), 43.1% (95% CI = 30.3% to 55.3%), 35.9% (95% CI = 23.8% to 48.2%), respectively, in the combined modality arm and 55.2% (95% CI = 41.6% to 66.9%), 30.3% (95% CI = 19.0% to 42.4%), 8.9% (95% CI = 3.3% to 18.1%), respectively, in the systemic treatment arm. Median OS was 45.6 months (95% CI = 30.3 to 67.8 months) in the combined modality arm vs 40.5 months (95% CI = 27.5 to 47.7 months) in the systemic treatment arm.
Conclusions: This phase II trial is the first randomized study demonstrating that aggressive local treatment can prolong OS in patients with unresectable colorectal liver metastases