Evidence map›Paper›PMID 28275392›Full record

ArticleEcancermedicalscience2017

Clinical response in patients with ovarian cancer treated with metronomic chemotherapy.

Herman Andrés Perroud, O Graciela Scharovsky, Viviana Rosa Rozados, Carlos María Alasino

Open access · goldAbstract read
In one paragraph

Article in Ecancermedicalscience, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.8field-weighted citation impact, top 15% 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

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Trial
  2. Review
  3. Article
  4. 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

4 authors at 3 institutions in 2 countries.

Herman Andrés PerroudExperimental Oncology Section, Institute of Experimental Genetics, School of Medical Sciences, National University of Rosario, Rosario 2000, Argentina; National Scientific and Technical Research Council (CONICET), Rosario 2000, Argentina.; Italian Hospital of Rosario, Department of Clinical Oncology, Rosario 2000, Argentina.
O Graciela ScharovskyExperimental Oncology Section, Institute of Experimental Genetics, School of Medical Sciences, National University of Rosario, Rosario 2000, Argentina; National Scientific and Technical Research Council (CONICET), Rosario 2000, Argentina.; Research Council of the National University of Rosario (CIUNR), Rosario 2000, Argentina.
Viviana Rosa RozadosExperimental Oncology Section, Institute of Experimental Genetics, School of Medical Sciences, National University of Rosario, Rosario 2000, Argentina.
Carlos María AlasinoItalian Hospital of Rosario, Department of Clinical Oncology, Rosario 2000, Argentina; Institute of Oncology of Rosario, Rosario 2000, Argentina.
National University of Rosario · ARInstituto de Oncología de Rosario · ARNational Research Council · RO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ovarian cancer (OC) is the leading cause of death from gynaecological cancer. It is extremely hard to diagnose in the early stages and around 70% of patients present with advanced disease. Metronomic chemotherapy (MCT) is described as the chronic administration of, generally low, equally spaced, doses of chemotherapeutic drugs with therapeutic efficacy and low toxicity. This is an effective and low-cost way to treat several types of tumours, including ovarian cancer. Here, we present six cases of advanced ovarian cancer treated with MCT with low doses of cyclophosphamide, which showed clinical response and stable disease.

Indexed as

cyclophosphamidemetronomic chemotherapyovarian cancer

Identifiers

PMID28275392
PMCPMC5336390
OpenAlexW2592557547

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.