Evidence map›Paper›PMID 37148829›Full record

ArticleClinics (Sao Paulo, Brazil)2023

Preliminary outcomes of five-year survival for ovarian malignancies in profiled Serbian Oncology Centre.

Bojana Gutic, Tatjana Bozanovic, Aljosa Mandic, Stefan Dugalic, Jovana Todorovic, Miroslava Gojnic Dugalic, Demet Sengul, Dzenana A Detanac, Ilker Sengul, Dzemail Detanac and 2 more

Abstract read
In one paragraph

Article in Clinics (Sao Paulo, Brazil), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

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  14. Ergonomics appraisals in operating rooms.Clinics (Sao Paulo, Brazil) · 2024
    Article
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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

12 authors.

Bojana GuticOncology Institute of Vojvodina, Sremska Kamenica, Faculty of Medicine University of Novi Sad, Faculty of Medicine University of Belgrade, Belgrade, Serbia.
Tatjana BozanovicDepartment of Gynecology and Obstetrics, University Clinical Center of Serbia, Clinic for Gynecology and Obstetrics, Faculty of Medicine University of Belgrade, Belgrade, Serbia.
Aljosa MandicOncology Institute of Vojvodina, Sremska Kamenica, Faculty of Medicine University of Novi Sad, Faculty of Medicine University of Belgrade, Belgrade, Serbia.
Stefan DugalicDepartment of Gynecology and Obstetrics, University Clinical Center of Serbia, Clinic for Gynecology and Obstetrics, Faculty of Medicine University of Belgrade, Belgrade, Serbia.
Jovana TodorovicInstitute for Social Medicine, University of Belgrade, Belgrade, Serbia.
Miroslava Gojnic DugalicDepartment of Gynecology and Obstetrics, University Clinical Center of Serbia, Clinic for Gynecology and Obstetrics, Faculty of Medicine University of Belgrade, Belgrade, Serbia.
Demet SengulDepartment of Pathology, Faculty of Medicine, Giresun University, Giresun, Turkey.
Dzenana A DetanacDepartment of Ophthalmology, General Hospital Novi Pazar, Novi Pazar, Serbia.
Ilker SengulDivision of Endocrine Surgery, Faculty of Medicine, Giresun University, Giresun, Turkey; Department of General Surgery, Faculty of Medicine, Giresun University, Giresun, Turkey. Electronic address: ilker.sengul.52@gmail.com.
Dzemail DetanacDepartment of General Surgery, General Hospital Novi Pazar, Novi Pazar, Serbia.
Tugrul KesiciogluDepartment of General Surgery, Faculty of Medicine, Giresun University, Giresun, Turkey.
José Maria Soares JuniorDisciplina de Ginecologia, Departamento de Obstetrícia e Ginecologia, Hospital das Clínicas, Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP, Brasil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe present study purposed to determine characteristics of ovarian carcinoma and to analyze predictors of survival in patients with ovarian carcinoma.

methodA retrospective cohort study was conducted including the patients with diagnosed ovarian carcinoma treated at the Clinic for Operative Oncology, Oncology Institute of Vojvodina in the period from January 2012 to December 2016. Seventy-two women with ovarian carcinoma were included in the analysis. The data about the histological type of tumor, disease stage, treatment, lymphatic infiltration, and surgical procedure were collected retrospectively, using the database of the institution where the research was conducted (BirPis 21 SRC Infonet DOO ‒ Information System Oncology Institute of Vojvodina). Descriptive statistics and multivariate analysis using Cox proportional hazards model were performed.

resultsThe univariate Cox regression analysis identified histology, tumor grade, FIGO (International Federation of Gynecology and Obstetrics) stage, NACT (Neoadjuvant Chemotherapy), number of therapy cycles, type of surgery, and chemotherapy response as independent predictors of mortality. Finally, the type of tumor and chemotherapy response had an increased hazard ratio for mortality in the multivariate Cox regression model. Herewith, the percentage of high-grade, advanced-stage ovarian cancer patients with complete response to chemotherapy, absence of recurrent disease, and lymphovascular space invasion were significant predictors of survival in patients with ovarian carcinoma.

conclusionsHerein, emerging data regarding precision medicine and molecular-based personalized treatments are promising and will likely modify the way the authors provide multiple lines of treatments in the near future.

Indexed as

Ovarian NeoplasmsCarcinoma, Ovarian EpithelialChemotherapy, AdjuvantFemaleHumansNeoadjuvant TherapyNeoplasm StagingRetrospective StudiesSerbiaCarcinomaHistopathologyOncologyOvaryPathologySurgery

Identifiers

PMID37148829
PMCPMC10757273

What OpenQuestion holds

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Registered trials

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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.