Evidence map›Paper›PMID 26227259›Full record

ArticleRadiation oncology (London, England)2015

A proliferation saturation index to predict radiation response and personalize radiotherapy fractionation.

Sotiris Prokopiou, Eduardo G Moros, Jan Poleszczuk, Jimmy Caudell, Javier F Torres-Roca, Kujtim Latifi, Jae K Lee, Robert Myerson, Louis B Harrison, Heiko Enderling

Open access · goldAbstract readValidation Study
In one paragraph

Article in Radiation oncology (London, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed
9.7field-weighted citation impact, top 1% 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

62 citing papers in PubMed, 132 citations in OpenAlex.

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  11. Identifiability and model selection frameworks for models of high-grade glioma response to chemoradiation.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025
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2 more citing papers are in PubMed but not listed here.

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

10 authors at 2 institutions in 1 country.

Sotiris ProkopiouDepartments of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center & Research Institute, 12902 Magnolia Drive, Tampa, FL, 33612, USA.
Eduardo G MorosDepartment of Radiation Oncology, H. Lee Moffitt Cancer Center & Research Institute, 12902 Magnolia Drive, Tampa, FL, 33612, USA.
Jan PoleszczukDepartments of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center & Research Institute, 12902 Magnolia Drive, Tampa, FL, 33612, USA.
Jimmy CaudellDepartment of Radiation Oncology, H. Lee Moffitt Cancer Center & Research Institute, 12902 Magnolia Drive, Tampa, FL, 33612, USA.
Javier F Torres-RocaDepartment of Radiation Oncology, H. Lee Moffitt Cancer Center & Research Institute, 12902 Magnolia Drive, Tampa, FL, 33612, USA.
Kujtim LatifiDepartment of Radiation Oncology, H. Lee Moffitt Cancer Center & Research Institute, 12902 Magnolia Drive, Tampa, FL, 33612, USA.
Jae K LeeDepartment of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center & Research Institute, 12902 Magnolia Drive, Tampa, FL, USA.
Robert MyersonDepartment of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, USA.
Louis B HarrisonDepartment of Radiation Oncology, H. Lee Moffitt Cancer Center & Research Institute, 12902 Magnolia Drive, Tampa, FL, 33612, USA.
Heiko EnderlingDepartments of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center & Research Institute, 12902 Magnolia Drive, Tampa, FL, 33612, USA. Heiko.Enderling@Moffitt.org.
Moffitt Cancer Center · USWashington University in St. Louis · US

Funding

TRANSLATIONAL RESEARCHP30CA076292 · NCI · UNIVERSITY OF SOUTH FLORIDA · PI KENNETH Lynn WRIGHT · 1998 to 2026
$93.5M
Integrative Molecular Epidemiology WorkshopR25CA174664 · NCI · AMERICAN ASSOCIATION FOR CANCER RESEARCH · PI Shelley S Tworoger · 2013 to 2026
$2.8M
NCI NIH HHS P30 CA076292NCI NIH HHS R25 CA174664
6 · The paper itself

Abstract

backgroundAlthough altered protocols that challenge conventional radiation fractionation have been tested in prospective clinical trials, we still have limited understanding of how to select the most appropriate fractionation schedule for individual patients. Currently, the prescription of definitive radiotherapy is based on the primary site and stage, without regard to patient-specific tumor or host factors that may influence outcome. We hypothesize that the proportion of radiosensitive proliferating cells is dependent on the saturation of the tumor carrying capacity. This may serve as a prognostic factor for personalized radiotherapy (RT) fractionation.

methodsWe introduce a proliferation saturation index (PSI), which is defined as the ratio of tumor volume to the host-influenced tumor carrying capacity. Carrying capacity is as a conceptual measure of the maximum volume that can be supported by the current tumor environment including oxygen and nutrient availability, immune surveillance and acidity. PSI is estimated from two temporally separated routine pre-radiotherapy computed tomography scans and a deterministic logistic tumor growth model. We introduce the patient-specific pre-treatment PSI into a model of tumor growth and radiotherapy response, and fit the model to retrospective data of four non-small cell lung cancer patients treated exclusively with standard fractionation. We then simulate both a clinical trial hyperfractionation protocol and daily fractionations, with equal biologically effective dose, to compare tumor volume reduction as a function of pretreatment PSI.

resultsWith tumor doubling time and radiosensitivity assumed constant across patients, a patient-specific pretreatment PSI is sufficient to fit individual patient response data (R(2) = 0.98). PSI varies greatly between patients (coefficient of variation >128 %) and correlates inversely with radiotherapy response. For this study, our simulations suggest that only patients with intermediate PSI (0.45-0.9) are likely to truly benefit from hyperfractionation. For up to 20 % uncertainties in tumor growth rate, radiosensitivity, and noise in radiological data, the absolute estimation error of pretreatment PSI is <10 % for more than 75 % of patients.

conclusionsRoutine radiological images can be used to calculate individual PSI, which may serve as a prognostic factor for radiation response. This provides a new paradigm and rationale to select personalized RT dose-fractionation.

Indexed as

Dose Fractionation, RadiationDose-Response Relationship, RadiationAlgorithmsCarcinoma, Non-Small-Cell LungCell DivisionCell HypoxiaComputer SimulationHumansHydrogen-Ion ConcentrationImmunologic SurveillanceLung NeoplasmsModels, BiologicalPrecision MedicineRadiation ToleranceRandom AllocationRelative Biological Effectiveness

Identifiers

PMID26227259
PMCPMC4521490
OpenAlexW1512206713

What OpenQuestion holds

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LicenceCC BY
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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.