Evidence map›Paper›PMID 35620200›Full record

ReviewCurrent research in pharmacology and drug discovery2022

Evaluation of synergism in drug combinations and reference models for future orientations in oncology.

Diana Duarte, Nuno Vale

Open access · goldAbstract readReview
In one paragraph

Review in Current research in pharmacology and drug discovery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 170 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
170citing papers in PubMed, 1 pooled it
37.3field-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

170 citing papers in PubMed, 1 synthesis or guideline pooled it, 279 citations in OpenAlex.

  1. Pooled it
  2. Article
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  5. Article
  6. Article
  7. Discovery of a peripherally restricted αCell reports. Medicine · 2026
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  8. Lessons From Drug Discovery for Cryoprotective Agent Design: An AI-Oriented Perspective.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  9. Article
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  11. Exploring Mechanistic Targets ofInternational journal of molecular sciences · 2026
    Article
  12. Article
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  15. Cancer Evolvability Determines Therapy Outcomes.bioRxiv : the preprint server for biology · 2026
    Article
  16. Article
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  18. Review
  19. Article
  20. Article

110 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

2 authors at 1 institution in 1 country.

Diana DuarteOncoPharma Research Group, Center for Health Technology and Services Research (CINTESIS), Rua Dr. Plácido da Costa, 4200-450, Porto, Portugal.
Nuno ValeOncoPharma Research Group, Center for Health Technology and Services Research (CINTESIS), Rua Dr. Plácido da Costa, 4200-450, Porto, Portugal.
Universidade do Porto · PT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current cancer therapy includes a variety of strategies that can comprise only one type of treatment or a combination of multiple treatments. Chemotherapy is still the gold standard for cancer therapy, though sometimes associated with undesired side effects and the development of drug resistance. For this reason, drug combination is an approach that has been proposed to overcome the problems related to monotherapy and several studies have already demonstrated the superiority of combined therapies compared to monotherapy. The main goal when designing and evaluating drug combinations is to achieve synergistic effects by demonstrating that the combined effects are greatly superior to the expected from the additive effects of the single drugs, allowing for dosage reduction and therefore decreasing toxicity. Nevertheless, synergism quantification is not a simple task due to the different definitions of additivity and over the years several reference models have been proposed based on different assumptions and with different mathematical frameworks. In this review, we begin to cover the available treatment options for cancer therapy, with emphasis on the importance of drug combinations in cancer therapy. We next describe the classical reference models that have been proposed for synergism evaluation, usually classified as effect-based and dose-effect based methods, with a brief analysis of the current limitations of these models. We also describe here the novel methods for the accurate quantification of drug interactions in combined treatments. At the end of this manuscript, we covered some of the most recent preclinical and clinical combination studies that reflect the importance of the appropriate, accurate and precise application of the concepts and methodologies here described for the evaluation of synergism.

Indexed as

BlissCombination indexDrug combinationLoeweOncologySynergy

Identifiers

PMID35620200
PMCPMC9127325
OpenAlexW4280589597

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.