Evidence map›Paper›PMID 30627814›Full record

ArticleThe AAPS journal2019

Survival Prolongation Index as a Novel Metric to Assess Anti-Tumor Activity in Xenograft Models.

Fiona Chandra, Lihi Zaks, Andy Zhu

Abstract read
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In one paragraph

Article in The AAPS journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 55% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. 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

3 authors at 2 institutions in 1 country.

Fiona ChandraTranslation Modeling and Simulation, DMPK, Takeda Pharmaceuticals, 35 Landsdowne St, Cambridge, Massachusetts, 02139, USA. fiona.a.chandra@gmail.com.
Lihi ZaksDepartment of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Andy ZhuTranslation Modeling and Simulation, DMPK, Takeda Pharmaceuticals, 35 Landsdowne St, Cambridge, Massachusetts, 02139, USA.
Takeda (United States) · USUniversity of Pennsylvania · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A single efficacy metric quantifying anti-tumor activity in xenograft models is useful in evaluating different tumors' drug sensitivity and dose-response of an anti-tumor agent. Commonly used metrics include the ratio of tumor volume in treated vs. control mice (T/C), tumor growth inhibition (TGI), ratio of area under the curve (AUC), and growth rate inhibition (GRI). However, these metrics have some limitations. In particular, for biologics with long half-lives, tumor volume (TV) of treated xenografts displays a delay in volume reduction (and in some cases, complete regression) followed by a growth rebound. These observed data cannot be described by exponential functions, which is the underlying assumption of TGI and GRI, and the fit depends on how long the tumor volumes are monitored. On the other hand, T/C and TGI only utilizes information from one chosen time point. Here, we propose a new metric called Survival Prolongation Index (SPI), calculated as the time for drug-treated TV to reach a certain size (e.g., 600 mm

Indexed as

AnimalsAntineoplastic AgentsCell Line, TumorDatasets as TopicHumansMiceModels, BiologicalNeoplasmsRetrospective StudiesSurvival AnalysisTime FactorsTumor BurdenXenograft Model Antitumor AssaysAntineoplastic Agentsantitumor activitytumor growth inhibitionxenograft

Identifiers

PMID30627814
OpenAlexW2909179839

What OpenQuestion holds

Textmetadata
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.