Evidence map›Paper›PMID 35681680›Full record

ArticleCancers2022

In Silico Investigations of Multi-Drug Adaptive Therapy Protocols.

Daniel S Thomas, Luis H Cisneros, Alexander R A Anderson, Carlo C Maley

Abstract read
In one paragraph

Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
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

13 citing papers in PubMed.

  1. Article
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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.

Daniel S ThomasArizona Cancer Evolution Center, Arizona State University, Tempe, AZ 85287, USA.
Luis H CisnerosArizona Cancer Evolution Center, Arizona State University, Tempe, AZ 85287, USA.ORCID 0000-0002-7890-1269
Alexander R A AndersonIntegrated Mathematical Oncology Department, Moffitt Cancer Center, Tampa, FL 33647, USA.ORCID 0000-0002-2536-4383
Carlo C MaleyArizona Cancer Evolution Center, Arizona State University, Tempe, AZ 85287, USA.ORCID 0000-0002-0745-7076

Funding

PHYLOGENIES of Barrett's Esophagus LineagesP01CA091955 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI GRADY, WILLIAM MALLORY · 2002 to 2019
$35.9M
Molecular, Cellular and Tissue Characterization UnitU2CCA233254 · NCI · DUKE UNIVERSITY · PI HWANG, E.SHELLEY, MALEY, CARLO · 2018 to 2023
$11.4M
The Role of the Microbiome in Cancer Suppression and Susceptibility Across SpeciesU54CA217376 · NCI · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI MALEY, CARLO · 2018 to 2022
$8.6M
Modeling Neoplastic Progression in Barrett's Esophagus - Renewal -2R01CA140657 · NCI · WISTAR INSTITUTE · PI Carlo Maley · 2009 to 2026
$5.0M
Eco-Evolutionary dynamics of NSCLC to immunotherapy: Response and ResistanceU01CA232382 · NCI · H. LEE MOFFITT CANCER CTR & RES INST · PI ANDERSON, ALEXANDER ROBERTSON ALLAN, ANTONIA, SCOTT J. · 2018 to 2022
$3.3M
NCI NIH HHS P01 CA091955NCI NIH HHS R01 CA140657NCI NIH HHS U01 CA232382NCI NIH HHS U2C CA233254NCI NIH HHS U54 CA217376
6 · The paper itself

Abstract

The standard of care for cancer patients aims to eradicate the tumor by killing the maximum number of cancer cells using the maximum tolerated dose (MTD) of a drug. MTD causes significant toxicity and selects for resistant cells, eventually making the tumor refractory to treatment. Adaptive therapy aims to maximize time to progression (TTP), by maintaining sensitive cells to compete with resistant cells. We explored both dose modulation (DM) protocols and fixed dose (FD) interspersed with drug holiday protocols. In contrast to previous single drug protocols, we explored the determinants of success of two-drug adaptive therapy protocols, using an agent-based model. In almost all cases, DM protocols (but not FD protocols) increased TTP relative to MTD. DM protocols worked well when there was more competition, with a higher cost of resistance, greater cell turnover, and when crowded proliferating cells could replace their neighbors. The amount that the drug dose was changed, mattered less. The more sensitive the protocol was to tumor burden changes, the better. In general, protocols that used as little drug as possible, worked best. Preclinical experiments should test these predictions, especially dose modulation protocols, with the goal of generating successful clinical trials for greater cancer control.

Indexed as

adaptive therapyagent-based modelcancerdose modulationdrug resistanceevolution

Identifiers

PMID35681680
PMCPMC9179496

What OpenQuestion holds

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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.