Evidence map›Paper›PMID 34797430›Full record

ArticleBulletin of mathematical biology2021

Intermittent Hormone Therapy Models Analysis and Bayesian Model Comparison for Prostate Cancer.

S Pasetto, H Enderling, R A Gatenby, R Brady-Nicholls

Open access · hybridAbstract read
In one paragraph

Article in Bulletin of mathematical biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.1field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Article
  3. Treatment of evolving cancers will require dynamic decision support.Annals of oncology : official journal of the European Society for Medical Oncology · 2023
    Review
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

S PasettoDepartment of Integrated Mathematical Oncology, H. Lee Moffitt Cancer and Research Institute, 12902 Magnolia Drive, Tampa, FL, 33612, USA. stefano.pasetto@moffitt.org.ORCID 0000-0002-4926-3704
H EnderlingDepartment of Integrated Mathematical Oncology, H. Lee Moffitt Cancer and Research Institute, 12902 Magnolia Drive, Tampa, FL, 33612, USA.
R A GatenbyDepartment of Integrated Mathematical Oncology, H. Lee Moffitt Cancer and Research Institute, 12902 Magnolia Drive, Tampa, FL, 33612, USA.
R Brady-NichollsDepartment of Integrated Mathematical Oncology, H. Lee Moffitt Cancer and Research Institute, 12902 Magnolia Drive, Tampa, FL, 33612, USA. renee.brady@moffitt.org.
Moffitt Cancer Center · US

Funding

The Physi(ologi)cal Microenvironment and its Role in Tumor Invasion and MetastaseU54CA143970 · NCI · H. LEE MOFFITT CANCER CTR & RES INST · PI GATENBY, ROBERT A · 2009 to 2014
$9.3M
Predicting patient-specific responses to personalize androgen deprivation therapy for prostate cancerR21CA234787 · NCI · H. LEE MOFFITT CANCER CTR & RES INST · PI ENDERLING, HEIKO, GATENBY, ROBERT A · 2019 to 2020
$422k
NCI NIH HHS R21 CA234787NCI NIH HHS U54 CA143970
6 · The paper itself

Abstract

The prostate is an exocrine gland of the male reproductive system dependent on androgens (testosterone and dihydrotestosterone) for development and maintenance. First-line therapy for prostate cancer includes androgen deprivation therapy (ADT), depriving both the normal and malignant prostate cells of androgens required for proliferation and survival. A significant problem with continuous ADT at the maximum tolerable dose is the insurgence of cancer cell resistance. In recent years, intermittent ADT has been proposed as an alternative to continuous ADT, limiting toxicities and delaying time-to-progression. Several mathematical models with different biological resistance mechanisms have been considered to simulate intermittent ADT response dynamics. We present a comparison between 13 of these intermittent dynamical models and assess their ability to describe prostate-specific antigen (PSA) dynamics. The models are calibrated to longitudinal PSA data from the Canadian Prospective Phase II Trial of intermittent ADT for locally advanced prostate cancer. We perform Bayesian inference and model analysis over the models' space of parameters on- and off-treatment to determine each model's strength and weakness in describing the patient-specific PSA dynamics. Additionally, we carry out a classical Bayesian model comparison on the models' evidence to determine the models with the highest likelihood to simulate the clinically observed dynamics. Our analysis identifies several models with critical abilities to disentangle between relapsing and not relapsing patients, together with parameter intervals where the critical points' basin of attraction might be exploited for clinical purposes. Finally, within the Bayesian model comparison framework, we identify the most compelling models in the description of the clinical data.

Indexed as

Androgen AntagonistsProstatic NeoplasmsBayes TheoremCanadaHumansMaleMathematical ConceptsModels, BiologicalNeoplasm Recurrence, LocalProspective StudiesTestosteroneTreatment OutcomeAndrogen AntagonistsTestosteroneIntermittent hormone therapy modelsProstate cancer

Identifiers

PMID34797430
PMCPMC8604892
OpenAlexW3212373720

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.