Mitigating Study Power Loss Caused by Clinical Trial Disruptions Due to the COVID-19 Pandemic: Leveraging External Data via Propensity Score-Integrated Approaches

7031 Background: AML in older adults is associated with poor outcomes. The Moffitt Cancer Center AML Database was used to evaluate a very large cohort of patients (pts) age ≥ 70 with untreated AML to identify key prognostic variables affecting outcome. Methods: Overall survival (OS): Kaplan-Meier method and was compared across groups using the log-rank test. Association between OS and predictors: Cox regression model. Impact of participation of initial clinical trial on OS: Propensity score with stratified log-rank test. A predictive model for 12 month OS was developed using multiple logistic regression with backward elimination method. Results: Nine hundred eighty (980) pts were identified. M/F(%): 66/34. Median age at diagnosis: 75.7 years (range 70 – 95.7 years). De novo/secondary (%): 43/57. Fifty two % of pts had prior hematologic disease (AHD). Baseline karyotype at AML diagnosis: adverse in 31% and non-adverse in 58%. Baseline ECOG PS: 0-1 in 79%; ≥2 in 19%. Median OS was 7.1 months (95% CI 6.4 – 7.9) for the entire cohort. In the univariable model, factors associated with inferior survival included: secondary AML (sAML) status, poor-risk karyotype, ECOG ≥2, non HMA therapy (including clinical trials), Charlson Comorbidity Index ≥3, older age, increased WBC, decreased platelets (plts), and decreased hemoglobin (hgb). Independent negative predictors for OS in the multivariate model included sAML, poor-risk karyotype, ECOG ≥2, non-HMA initial therapy, older age, increased WBC, decreased plts, and decreased hgb. Propensity score matching revealed no significant difference in OS amongst pts receiving initial treatment on a clinical trial (median 7.8 months, 95% CI 6.4 – 10.4) vs not (median 7.0 months, 95% CI 6 –7.9). A model to predict OS at 12 month was developed in a subset of 446 pts. Independent predictive variables included karyotype, ECOG PS, AML type (de novo vs sAML), age, and WBC, with AUC of 0.78, indicating strong discriminatory capacity. Conclusions: In this largest reported cohort of AML pts age ≥ 70, prognostic modeling identifies differences in longer-term survival with conventional therapies, discriminating the highest risk subsets. Decision modeling to further assist choice of optimal therapies for these pts is in progress.

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Propensity score-integrated power prior approach for augmenting the control arm of a randomized controlled trial by incorporating multiple external data sources

Journal of Biopharmaceutical Statistics ◽

10.1080/10543406.2021.1998098 ◽

2021 ◽

pp. 1-12

Author(s):

Nelson Lu ◽

Chenguang Wang ◽

Wei-Chen Chen ◽

Heng Li ◽

Changhong Song ◽

...

Keyword(s):

Randomized Controlled Trial ◽

Propensity Score ◽

Controlled Trial ◽

Data Sources ◽

Randomized Controlled ◽

External Data ◽

Power Prior

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DEBATE-statistical analysis plans for observational studies

BMC Medical Research Methodology ◽

10.1186/s12874-019-0879-5 ◽

2019 ◽

Vol 19 (1) ◽

Cited By ~ 6

Author(s):

Bart Hiemstra ◽

Frederik Keus ◽

Jørn Wetterslev ◽

Christian Gluud ◽

Iwan C. C. van der Horst

Keyword(s):

Clinical Trial ◽

Clinical Trials ◽

Statistical Analysis ◽

Observational Study ◽

Observational Studies ◽

Data Driven ◽

Study Power ◽

Definition Of ◽

Main Message ◽

New Item

Abstract Background All clinical research benefits from transparency and validity. Transparency and validity of studies may increase by prospective registration of protocols and by publication of statistical analysis plans (SAPs) before data have been accessed to discern data-driven analyses from pre-planned analyses. Main message Like clinical trials, recommendations for SAPs for observational studies increase the transparency and validity of findings. We appraised the applicability of recently developed guidelines for the content of SAPs for clinical trials to SAPs for observational studies. Of the 32 items recommended for a SAP for a clinical trial, 30 items (94%) were identically applicable to a SAP for our observational study. Power estimations and adjustments for multiplicity are equally important in observational studies and clinical trials as both types of studies usually address multiple hypotheses. Only two clinical trial items (6%) regarding issues of randomisation and definition of adherence to the intervention did not seem applicable to observational studies. We suggest to include one new item specifically applicable to observational studies to be addressed in a SAP, describing how adjustment for possible confounders will be handled in the analyses. Conclusion With only few amendments, the guidelines for SAP of a clinical trial can be applied to a SAP for an observational study. We suggest SAPs should be equally required for observational studies and clinical trials to increase their transparency and validity.

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Systemic Corticosteroids and Mortality in Severe and Critical COVID-19 Patients in Wuhan, China

The Journal of Clinical Endocrinology & Metabolism ◽

10.1210/clinem/dgaa627 ◽

2020 ◽

Vol 105 (12) ◽

pp. e4230-e4239 ◽

Cited By ~ 4

Author(s):

Jianfeng Wu ◽

Jianqiang Huang ◽

Guochao Zhu ◽

Yihao Liu ◽

Han Xiao ◽

...

Keyword(s):

Clinical Trial ◽

Propensity Score ◽

Hospital Mortality ◽

Beneficial Effect ◽

Propensity Score Analysis ◽

Cox Model ◽

Controlled Clinical Trial ◽

Supporting Evidence ◽

Time Varying ◽

Systemic Corticosteroids

Abstract Background Systemic corticosteroids are now recommended in many treatment guidelines, although supporting evidence is limited to 1 randomized controlled clinical trial (RECOVERY). Objective To identify whether corticosteroids were beneficial to COVID-19 patients. Methods A total of 1514 severe and 249 critical hospitalized COVID-19 patients from 2 medical centers in Wuhan, China. Multivariable Cox models, Cox model with time-varying exposure and propensity score analysis (inverse-probability-of-treatment-weighting [IPTW] and propensity score matching [PSM]) were used to estimate the association of corticosteroid use with risk of in-hospital mortality in severe and critical cases. Results Corticosteroids were administered in 531 (35.1%) severe and 159 (63.9%) critical patients. Compared to the non-corticosteroid group, systemic corticosteroid use was not associated with beneficial effect in reducing in-hospital mortality in either severe cases (HR = 1.77; 95% CI, 1.08-2.89; P = 0.023), or critical cases (HR = 2.07; 95% CI, 1.08–3.98; P = 0.028). Findings were similar in time-varying Cox analysis. For patients with severe COVID-19 at admission, corticosteroid use was not associated with improved or harmful outcome in either PSM or IPTW analysis. For critical COVID-19 patients at admission, results were consistent with multivariable Cox model analysis. Conclusion Corticosteroid use was not associated with beneficial effect in reducing in-hospital mortality for severe or critical cases in Wuhan. Absence of the beneficial effect in our study in contrast to that observed in the RECOVERY clinical trial may be due to biases in observational data, in particular prescription by indication bias, differences in clinical characteristics of patients, choice of corticosteroid used, timing of initiation of treatment, and duration of treatment.

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Clinical trial participation as part of end-of-life (EOL) cancer care: Associations with medical care near death and bereaved caregivers’ mental health.

Journal of Clinical Oncology ◽

10.1200/jco.2012.30.15_suppl.9102 ◽

2012 ◽

Vol 30 (15_suppl) ◽

pp. 9102-9102

Author(s):

Andrea Catherine Phelps ◽

Baohui Zhang ◽

Holly Gwen Prigerson

Keyword(s):

Mental Health ◽

Clinical Trial ◽

Propensity Score ◽

Cancer Patients ◽

Advanced Cancer ◽

Chart Review ◽

Trial Participation ◽

Clinical Trial Participation ◽

Advanced Cancer Patients ◽

Eol Care

9102 Background: Clinical trial participation is necessary to improve existing therapies, encouraged by national guidelines, and common among advanced cancer patients. The relationships between trial participation and important EOL outcomes such as aggressive care are unknown. Methods: Coping with Cancer Study, an NCI-funded multicenter prospective cohort study of advanced cancer patients and their caregivers, enrolled September 2002 – February 2008. Patients were interviewed at baseline, and clinical trial participation was documented by chart review. Patients were followed to death, (median 4.4 months from baseline). Medical care and quality of life (QOL) in the last week of life was assessed by caregiver interview and chart review. Caregiver interview 6 months post-bereavement assessed QOL and mental health (Structured Clinical Interview for the DSM-IV). The primary outcome was aggressive EOL care (ventilation, resuscitation, or chemotherapy in the last week of life). Secondary outcomes were bereaved caregivers’ mental health and QOL. Propensity-score weighting balanced patient characteristics (e.g. clinical variables, EOL preferences) that differed by trial participation. Propensity-score weighted regression models estimated the effect of trial participation on outcomes. Results: Of 246 patients followed to death with non-missing propensity scores, 27 were clinical trial participants. In propensity-score weighted analyses, trial participation was significantly associated with aggressive EOL care [29.6% v 9.1%; adjusted OR (AOR), 12.14; 95% CI, 3.65-40.36], ICU admission, mechanical ventilation, chemotherapy, and a trend toward inferior QOL near death (p = 0.069). Of 180 matched caregivers, trial participation predicted less mental illness [AOR, 0.15; 95% CI 0.04-0.57], major depression [AOR, 0.25; 95% CI, 0.08-0.80], but was unassociated with QOL (p = 0.15) in adjusted analyses. Conclusions: Clinical trial participation is associated with increased risk of aggressive EOL care for advanced cancer patients, but better mental health for bereaved caregivers.

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