ArticleTranslational cancer research2019
Clinicopathologic factors associated with short-term survival in advanced epithelial ovarian cancer.
Article in Translational cancer research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed, 3 citations in OpenAlex.
- Synergistic antitumor effect of liposomal-based formulations of olaparib and topotecan in primary epithelial ovarian cancer cells.Cancer cell international · 2024Article
- Detection and analysis of multiple biomarkers in ovarian cancer: clinical significance in diagnosis, treatment, and prognosis evaluation.Gland surgery · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEpithelial ovarian cancer (EOC) is the most lethal gynaecological malignancy, and there is a deficiency of information in the literature on the early recognition of short-term survivor (STS). This study aimed to identify the clinicopathological factors associated with STS in late-stage EOC and to establish a predictive model to identify STS.
methodsSelected patients with International Federation of Gynecology and Obstetrics (FIGO) stage III or IV EOC were included in the study, and a retrospective analysis was performed. The characteristics of the patients who survived not more than 2 years (STS) were compared to those who survived at least 2 years (defined as long-term survivors, LTS). Binary logistic regression and receiver operating characteristic curve (ROC) were used to identify the independent prognostic factors associated with EOC and assess the predictive accuracy for STS.
resultsWe identified 254 patients with advanced EOC including 57 STS and 197 LTS. A univariate analysis revealed that STS had a tendency to have omental metastasis and larger tumor size, to be platinum resistant, to have non-serous histology, to undergo suboptimal cytoreduction, to have comorbidity, and to undergo primary chemotherapy less than 6 courses. Binary regression analysis revealed that tumor size (P=0.033), platinum resistance (P<0.001), non-serous histology (P=0.048) and number of primary chemotherapy (P=0.028) were significant independent predictors of STS. A developed predictive model using these predictors had an AUC =0.831; platinum resistance alone had an AUC =0.732.
conclusionsTumor size, omental metastasis, platinum resistance, non-serous histology, and number of primary chemotherapy are predictors associated with STS when controlling other confounding factors. Tumor size and omental metastasis may be considered novel, important prognostic factors for advanced EOC patients. Platinum resistance was the most important prognosticator for STS; hence, more work is needed for the early identification and treatment of these EOC patients.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.