scholarly journals Model-Based Meta-Analysis for Quantifying Paclitaxel Dose Response in Cancer Patients

2014 ◽  
Vol 3 (5) ◽  
pp. 115 ◽  
Author(s):  
D Lu ◽  
A Joshi ◽  
H Li ◽  
N Zhang ◽  
MM Ren ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Dose Response ◽  
Meta Analysis ◽  
Model Based

Body mass index and mortality in prostate cancer patients: a dose–response meta-analysis

2016 ◽  
Vol 19 (2) ◽  
pp. 122-131 ◽  
Author(s):  
S Zhong ◽  
X Yan ◽  
Y Wu ◽  
X Zhang ◽  
L Chen ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Body Mass Index ◽  
Cancer Patients ◽  
Body Mass ◽  
Dose Response ◽  
Meta Analysis

scholarly journals Circulating Vitamin D and Overall Survival in Breast Cancer Patients: A Dose-Response Meta-Analysis of Cohort Studies

2017 ◽  
Vol 17 (2) ◽  
pp. 217-225 ◽  
Author(s):  
Kejia Hu ◽  
David Frederick Callen ◽  
Jiayuan Li ◽  
Hong Zheng
Keyword(s):  
Breast Cancer ◽  
Vitamin D ◽  
Overall Survival ◽  
Cancer Patients ◽  
Dose Response ◽  
Fixed Effects ◽  
Meta Analysis ◽  
Breast Cancer Patients ◽  
Fixed Effects Model ◽  
Vitamin D Levels

Studies have shown that vitamin D could have a role in breast cancer survival; however, the evidence of the relationship between patients’ vitamin D levels and their survival has been inconsistent. This meta-analysis explores possible dose-response relationships between vitamin D levels and overall survival by allowing for differences in vitamin D levels among populations of the various studies. Studies relating vitamin D (25-OH-D [25-hydroxyvitamin D]) levels in breast cancer patients with their survival were identified by searching PubMed and Embase. A pooled HR (hazard ratio) comparing the highest with the lowest category of circulating 25-OH-D levels were synthesized using the Mantel-Haenszel method under a fixed-effects model. A two-stage fixed-effects dose-response model including both linear (a log-linear dose-response regression) and nonlinear (a restricted cubic spline regression) models were used to further explore possible dose-response relationships. Six studies with a total number of 5984 patients were identified. A pooled HR comparing the highest with the lowest category of circulating 25-OH-D levels under a fixed-effects model was 0.67 (95% confidence interval = 0.56-0.79, P < .001). Utilizing a dose-response meta-analysis, the pooled HR for overall survival in breast cancer patients was 0.994 (per 1 nmol/L), Pfor linear trend < .001. At or above a 23.3 nmol/L threshold, for a 10 nmol/L, 20 nmol/L, or 25 nmol/L increment in circulating 25-OH-D levels, the risk of breast cancer overall mortality decreased by 6%, 12%, and 14%, respectively. There was no significant nonlinearity in the relationship between overall survival and circulating 25-OH-D levels. Our findings suggest that there is a highly significant linear dose-response relationship between circulating 25-OH-D levels and overall survival in patients with breast cancer. However, better designed prospective cohort studies and clinical trials are needed to further confirm these findings.

scholarly journals Joining the Dots: Linking Disconnected Networks of Evidence Using Dose-Response Model-Based Network Meta-Analysis

2021 ◽  
Vol 41 (2) ◽  
pp. 194-208
Author(s):  
Hugo Pedder ◽  
Sofia Dias ◽  
Meg Bennetts ◽  
Martin Boucher ◽  
Nicky J. Welton
Keyword(s):  
Dose Response ◽  
Meta Analysis ◽  
Relative Effectiveness ◽  
Data Sets ◽  
Response Relationship ◽  
Phase Ii Trials ◽  
Dose Response Relationship ◽  
Data Set ◽  
Model Based ◽  
Multiple Doses

Background Network meta-analysis (NMA) synthesizes direct and indirect evidence on multiple treatments to estimate their relative effectiveness. However, comparisons between disconnected treatments are not possible without making strong assumptions. When studies including multiple doses of the same drug are available, model-based NMA (MBNMA) presents a novel solution to this problem by modeling a parametric dose-response relationship within an NMA framework. In this article, we illustrate several scenarios in which dose-response MBNMA can connect and strengthen evidence networks. Methods We created illustrative data sets by removing studies or treatments from an NMA of triptans for migraine relief. We fitted MBNMA models with different dose-response relationships. For connected networks, we compared MBNMA estimates with NMA estimates. For disconnected networks, we compared MBNMA estimates with NMA estimates from an “augmented” network connected by adding studies or treatments back into the data set. Results In connected networks, relative effect estimates from MBNMA were more precise than those from NMA models (ratio of posterior SDs NMA v. MBNMA: median = 1.13; range = 1.04–1.68). In disconnected networks, MBNMA provided estimates for all treatments where NMA could not and were consistent with NMA estimates from augmented networks for 15 of 18 data sets. In the remaining 3 of 18 data sets, a more complex dose-response relationship was required than could be fitted with the available evidence. Conclusions Where information on multiple doses is available, MBNMA can connect disconnected networks and increase precision while making less strong assumptions than alternative approaches. MBNMA relies on correct specification of the dose-response relationship, which requires sufficient data at different doses to allow reliable estimation. We recommend that systematic reviews for NMA search for and include evidence (including phase II trials) on multiple doses of agents where available.

scholarly journals Circulating vitamin D level and mortality in prostate cancer patients: a dose–response meta-analysis

2018 ◽  
Vol 7 (12) ◽  
pp. R294-R303 ◽  
Author(s):  
Zhen-yu Song ◽  
Qiuming Yao ◽  
Zhiyuan Zhuo ◽  
Zhe Ma ◽  
Gang Chen
Keyword(s):  
Prostate Cancer ◽  
Vitamin D ◽  
Cancer Patients ◽  
Dose Response ◽  
Protective Factor ◽  
Meta Analysis ◽  
Random Effect Model ◽  
Hydroxyvitamin D ◽  
Risk Of Death ◽  
25 Hydroxyvitamin D

Previous studies investigating the association of circulating 25-hydroxyvitamin D level with prognosis of prostate cancer yielded controversial results. We conducted a dose–response meta-analysis to elucidate the relationship. PubMed and EMBASE were searched for eligible studies up to July 15, 2018. We performed a dose–response meta-analysis using random-effect model to calculate the summary hazard ratio (HR) and 95% CI of mortality in patients with prostate cancer. Seven eligible cohort studies with 7808 participants were included. The results indicated that higher vitamin D level could reduce the risk of death among prostate cancer patients. The summary HR of prostate cancer-specific mortality correlated with an increment of every 20 nmol/L in circulating vitamin D level was 0.91, with 95% CI 0.87–0.97, P = 0.002. The HR for all-cause mortality with the increase of 20 nmol/L vitamin D was 0.91 (95% CI: 0.84–0.98, P = 0.01). Sensitivity analysis suggested the pooled HRs were stable and not obviously changed by any single study. No evidence of publications bias was observed. This meta-analysis suggested that higher 25-hydroxyvitamin D level was associated with a reduction of mortality in prostate cancer patients and vitamin D is an important protective factor in the progression and prognosis of prostate cancer.

Clinical dose–response for a broad set of biological products: A model-based meta-analysis

2017 ◽  
Vol 27 (9) ◽  
pp. 2694-2721 ◽  
Author(s):  
Joseph Wu ◽  
Anindita Banerjee ◽  
Bo Jin ◽  
Sandeep M Menon ◽  
Steven W Martin ◽  
...  
Keyword(s):  
Small Molecules ◽  
Dose Response ◽  
Meta Analysis ◽  
Small Sample ◽  
Model Parameters ◽  
Maximal Effect ◽  
Clinical Dose ◽  
Model Based ◽  
Effect Model ◽  
Dose Ranging

Characterizing clinical dose–response is a critical step in drug development. Uncertainty in the dose–response model when planning a dose-ranging study can often undermine efficiency in both the design and analysis of the trial. Results of a previous meta-analysis on a portfolio of small molecule compounds from a large pharmaceutical company demonstrated a consistent dose–response relationship that was well described by the maximal effect model. Biologics are different from small molecules due to their large molecular sizes and their potential to induce immunogenicity. A model-based meta-analysis was conducted on the clinical efficacy of 71 distinct biologics evaluated in 91 placebo-controlled dose–response studies published between 1995 and 2014. The maximal effect model, arising from receptor occupancy theory, described the clinical dose–response data for the majority of the biologics (81.7%, n = 58). Five biologics (7%) with data showing non-monotonic trend assuming the maximal effect model were identified and discussed. A Bayesian model-based hierarchical approach using different joint specifications of prior densities for the maximal effect model parameters was used to meta-analyze the whole set of biologics excluding these five biologics ( n = 66). Posterior predictive distributions of the maximal effect model parameters were reported and they could be used to aid the design of future dose-ranging studies. Compared to the meta-analysis of small molecules, the combination of fewer doses, narrower dosing ranges, and small sample sizes further limited the information available to estimate clinical dose–response among biologics.

scholarly journals Methods to assess evidence consistency in dose‐response model based network meta‐analysis

2021 ◽  
Author(s):  
Hugo Pedder ◽  
Sofia Dias ◽  
Martin Boucher ◽  
Meg Bennetts ◽  
David Mawdsley ◽  
...  
Keyword(s):  
Dose Response ◽  
Meta Analysis ◽  
Response Model ◽  
Model Based

Thrombosis in Cancer Patients Treated with Hematopoietic Growth Factors - A Meta-Analysis

1996 ◽  
Vol 75 (02) ◽  
pp. 368-371 ◽  
Author(s):  
T Barbul ◽  
G Finazzi ◽  
A Grassi ◽  
R Marchioli
Keyword(s):  
Cancer Patients ◽  
Case Reports ◽  
Meta Analysis ◽  
Case Series ◽  
Hematopoietic Growth Factors ◽  
Patients With Cancer ◽  
Cytotoxic Treatment ◽  
Pertinent Data ◽  
Thrombotic Complications ◽  
Vascular Occlusions

SummaryHematopoietic colony-stimulating factors (CSFs) are largely used in patients with cancer undergoing cytotoxic treatment to accelerate neutrophil recovery and decrease the incidence of febrile neutropenia. Clinical practice guidelines for their use have been recently established (1), taking into account clinical benefit, but also cost and toxicity. Vascular occlusions have been recently reported among the severe reactions associated with the use of CSFs, in anedoctal case reports (2, 3), consecutive case series (4) and randomized clinical trial (5, 6). However, the role of CSFs in the pathogenesis of thrombotic complications is difficult to ascertain, because pertinent data are scanty and widely distributed over a number of heterogenous investigations. We report here a systematic review of relevant articles, with the aims to estimate the prevalence of thrombosis associated with the use of CSFs and to assess if this rate is significantly higher than that observed in cancer patients not receiving CSFs.

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