Evidence map›Paper›PMID 33562443›Full record

ReviewCancers2021

Emerging Trends in Neoadjuvant Chemotherapy for Ovarian Cancer.

Ami Patel, Puja Iyer, Shinya Matsuzaki, Koji Matsuo, Anil K Sood, Nicole D Fleming

Open access · goldAbstract readReview
In one paragraph

Review in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 1 pooled it
8.5field-weighted citation impact, top 2% 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

31 citing papers in PubMed, 1 synthesis or guideline pooled it, 56 citations in OpenAlex.

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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

6 authors at 3 institutions in 2 countries.

Ami PatelDepartment of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Puja IyerDepartment of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Shinya MatsuzakiDepartment of Obstetrics and Gynecology, Osaka University Graduate School of Medicine, Osaka 565-0871, Japan.ORCID 0000-0001-5725-9994
Koji MatsuoDepartment of Obstetrics and Gynecology, Osaka University Graduate School of Medicine, Osaka 565-0871, Japan.
Anil K SoodDepartment of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Nicole D FlemingDepartment of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.ORCID 0000-0003-1785-4072
The University of Texas MD Anderson Cancer Center · USThe University of Osaka · JPUniversity of Southern California · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epithelial ovarian cancer remains a leading cause of death amongst all gynecologic cancers despite advances in surgical and medical therapy. Historically, patients with ovarian cancer underwent primary tumor reductive surgery followed by postoperative chemotherapy; however, neoadjuvant chemotherapy followed by interval tumor reductive surgery has gradually become an alternative approach for patients with advanced-stage ovarian cancer for whom primary tumor reductive surgery is not feasible. Decision-making about the use of these approaches has not been uniform. Hence, it is essential to identify patients who can benefit most from neoadjuvant chemotherapy followed by interval tumor reductive surgery. Several prospective and retrospective studies have proposed potential models to guide upfront decision-making for patients with advanced ovarian cancer. In this review, we summarize important decision-making models that can improve patient selection for personalized treatment. Models based on clinical factors (clinical parameters, radiology studies and laparoscopy scoring) and molecular markers (circulating and tumor-based) are useful, but laparoscopic staging is among the most informative diagnostic methods for upfront decision-making in patients medically fit for surgery. Further research is needed to explore more reliable models to determine personalized treatment for advanced epithelial ovarian cancer.

Indexed as

epithelial ovarian cancerinterval tumor reductive surgerylaparoscopy scoringmolecular markersneoadjuvant chemotherapyoptimal cytoreductionpersonalized treatmentradiology-based modelstargeted therapytumor-based genetic markers

Identifiers

PMID33562443
PMCPMC7915369
OpenAlexW3127855885

What OpenQuestion holds

Textmetadata
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.