Early change in tumour size predicts overall survival in patients with first-line metastatic breast cancer

Tate, Sonya C.; Andre, Valérie; Enas, Nathan; Ribba, Benjamin; Gueorguieva, Ivelina

doi:10.1016/j.ejca.2016.07.009

Cited by 17 publications

(14 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A number of published studies have modeled OS based on tumor kinetics in cancer patients treated with traditional chemotherapy or non-IO therapies. 6,[26][27][28][29] Our study is the first reported study that linked tumor kinetics to OS by using quantitative modeling for IO therapeutics. In contrast to previous studies, our model utilized the entire longitudinal tumor kinetic profile rather than a single timepoint or derived variable (e.g., time to tumor growth) as a predictor of OS.…”

Section: Discussionmentioning

confidence: 91%

See 1 more Smart Citation

Population Modeling of Tumor Kinetics and Overall Survival to Identify Prognostic and Predictive Biomarkers of Efficacy for Durvalumab in Patients With Urothelial Carcinoma

Zheng

Narwal²,

Jin

et al. 2018

Clin Pharma and Therapeutics

View full text Add to dashboard Cite

Durvalumab is an anti‐PD‐L1 monoclonal antibody approved for patients with locally advanced or metastatic urothelial carcinoma (UC) that has progressed after platinum‐containing chemotherapy. A population tumor kinetic model, coupled with dropout and survival models, was developed to describe longitudinal tumor size data and predict overall survival in UC patients treated with durvalumab (NCT01693562) and to identify prognostic and predictive biomarkers of clinical outcomes. Model‐based covariate analysis identified liver metastasis as the most influential factor for tumor growth and immune‐cell PD‐L1 expression and baseline tumor burden as predictive factors for tumor killing. Tumor or immune‐cell PD‐L1 expression, liver metastasis, baseline hemoglobin, and albumin levels were identified as significant covariates for overall survival. These model simulations provided further insights into the impact of PD‐L1 cutoff values on treatment outcomes. The modeling framework can be a useful tool to guide patient selection and enrichment strategies for immunotherapies across various cancer indications.

show abstract

Section: Discussionmentioning

confidence: 91%

“…A number of published studies have modeled OS based on tumor kinetics in cancer patients treated with traditional chemotherapy or non‐IO therapies . Our study is the first reported study that linked tumor kinetics to OS by using quantitative modeling for IO therapeutics.…”

Section: Discussionmentioning

confidence: 99%

Population Modeling of Tumor Kinetics and Overall Survival to Identify Prognostic and Predictive Biomarkers of Efficacy for Durvalumab in Patients With Urothelial Carcinoma

Zheng

Narwal²,

Jin

et al. 2018

Clin Pharma and Therapeutics

View full text Add to dashboard Cite

show abstract

“…Finally, the initial response of the primary tumour to a given chemotherapy is also a powerful prognostic indicator for subsequent development of metastases. Data from the International Metastatic Renal Cell Carcinoma (mRCC) Database Consortium showed that solitary versus multiple metastases were commoner in long‐term survivors (ratio 0.3 vs. 0.2) treated with targeted agents, mainly VEGF and mTOR inhibitors .…”

Section: Metastatic Risk Assessmentmentioning

confidence: 99%

“…Although the data from 18 FDG PET remains controversial 40,41 entropy measures from histogram analyses of MRI based tumour ADC can predict positive nodal status in rectal cancers 42 and in gastric cancers, while in soft-tissue sarcomas, first order statistics from ADC, which relate to signal variability and to entropy and dissimilarity, were higher in high grade tumours. 43 Finally, the initial response of the primary tumour to a given chemotherapy is also a powerful prognostic indicator [44][45][46][47] for subsequent development of metastases. Data from the International Metastatic Renal Cell Carcinoma (mRCC) Database Consortium showed that solitary versus multiple metastases were commoner in long-term survivors (ratio 0.3 vs. 0.2) treated with targeted agents, mainly VEGF and mTOR inhibitors.…”

Section: Metastatic Risk Assessmentmentioning

confidence: 99%

A risk‐based approach to identifying oligometastatic disease on imaging

deSouza

Tempany

2018

Intl Journal of Cancer

View full text Add to dashboard Cite

Recognition of <3 metastases in <2 organs, particularly in cancers with a known predisposition to oligometastatic disease (OMD) (colorectal, prostate, renal, sarcoma and lung), offers the opportunity to focally treat the lesions identified and confers a survival advantage. The reliability with which OMD is identified depends on the sensitivity of the imaging technique used for detection and may be predicted from phenotypic and genetic factors of the primary tumour, which determine metastatic risk. Whole-body or organ-specific imaging to identify oligometastases requires optimization to achieve maximal sensitivity. Metastatic lesions at multiple locations may require a variety of imaging modalities for best visualisation because the optimal image contrast is determined by tumour biology. Newer imaging techniques used for this purpose require validation. Additionally, rationalisation of imaging strategies is needed, particularly with regard to timing of imaging and follow-up studies. This article reviews the current evidence for the use of imaging for recognising OMD and proposes a risk-based roadmap for identifying patients with true OMD, or at risk of metastatic disease likely to be OM.

show abstract

“…Once established and validated, mechanistic PK/PD models offer a series of in silico related possibilities covering from optimizing response follow‐up designs and exploring alternative therapeutic scenarios, to personalize treatments based on late predictions from early clinical longitudinal response . Even though BC is a widely studied disease, PK/PD modelling efforts in BC have been focused on advanced or metastatic stages of the disease, relating tumour size (TS) at a certain time point with survival . However, modelling exercises applied to earlier stages of the disease can have a greater impact on the patients' outcome.…”

Section: Introductionmentioning

confidence: 99%

Assessing the impact of the addition of dendritic cell vaccination to neoadjuvant chemotherapy in breast cancer patients: A model‐based characterization approach

Solans

Cerio

Elizalde

et al. 2019

Brit J Clinical Pharma

View full text Add to dashboard Cite

Aims: Immunotherapy is a rising alternative to traditional treatment in breast cancer (BC) patients in order to transform cold into hot immune enriched tumours and improve responses and outcome. A computational modelling approach was applied to quantify modulation effects of immunotherapy and chemotherapy response on tumour shrinkage and progression-free survival (PFS) in naïve BC patients.Methods: Eighty-three Her2-negative BC patients were recruited for neoadjuvant chemotherapy with or without immunotherapy based on dendritic cell vaccination.Sequential tumour size measurements were modelled using nonlinear mixed effects modelling and linked to PFS. Data from another set of patients (n = 111) were used to validate the model.Results: Tumour size profiles over time were linked to biomarker dynamics and PFS. The immunotherapy effect was related to tumour shrinkage (P < .05), with the shrinkage 17% (95% confidence interval: 2-23%) being higher in vaccinated patients, confirmed by the finding that pathological complete response rates in the breast were higher in the vaccinated compared to the control group (25.6% vs 13.6%; P = .04). The whole tumour shrinkage time profile was the major prognostic factor associated to PFS (P < .05), and therefore, immunotherapy influences indirectly on PFS, showing a trend in decreasing the probability of progression with increased vaccine effects.Tumour subtype was also associated with PFS (P < .05), showing that luminal A BC patients have better prognosis.Conclusions: Dendritic cell-based immunotherapy is effective in decreasing tumour size. The semi-mechanistic validated model presented allows the quantification of the immunotherapy treatment effects on tumour shrinkage and establishes the relationship between the dynamics of tumour size and PFS.

show abstract

Early change in tumour size predicts overall survival in patients with first-line metastatic breast cancer

Cited by 17 publications

References 30 publications

Population Modeling of Tumor Kinetics and Overall Survival to Identify Prognostic and Predictive Biomarkers of Efficacy for Durvalumab in Patients With Urothelial Carcinoma

Population Modeling of Tumor Kinetics and Overall Survival to Identify Prognostic and Predictive Biomarkers of Efficacy for Durvalumab in Patients With Urothelial Carcinoma

A risk‐based approach to identifying oligometastatic disease on imaging

Assessing the impact of the addition of dendritic cell vaccination to neoadjuvant chemotherapy in breast cancer patients: A model‐based characterization approach

Contact Info

Product

Resources

About