Evidence map›Paper›PMID 31572007›Full record

ArticleCancer management and research2019

Beyond The T/C Ratio: Old And New Anticancer Activity Scores In Vivo.

Paolo Ubezio

Abstract read
In one paragraph

Article in Cancer management and research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. 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

1 author.

Paolo UbezioBiophysics Unit, Department of Oncology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.ORCID 0000-0003-0412-9891

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Assessing the efficacy of anticancer agents in animal models remains a necessary step in the development of new treatment options and plays an important role in their optimization and comparison. Often, however, interpretation of the results is flawed by excessive trust in scores traditionally handed down, but whose origin and limitations have been lost. Here I examine the theories and assumptions underlying the most common rating scales, suggesting improvements to the old scores and proposing the adoption of multi-parameter analysis and interpretation of the results, considering different time-windows. I examined case examples of different scenarios of antiproliferative effects induced by treatment, demonstrating that common scores fail to distinguish between completely different responses to treatment or, in other circumstances, indicate a different outcome when the response is the same. I found that a combination of parameters, including the percent tumor growth between the start and end of treatment, the relative tumor burden at nadir and the absolute growth delay, may distinguish among the different cases and support a correct interpretation of the antitumor response. All these parameters can be derived from individual tumor growth curves in a simple way, without any change to common experimental procedures.

Indexed as

anticancer activitycell killingcell proliferationpreclinical testingT/C ratiotreatment evaluationtumor growth curvestumor growth delay

Identifiers

PMID31572007
PMCPMC6756833

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.