Menopausal status strongly influences the utility of predictive models in differential diagnosis of ovarian tumors: An external validation of selected diagnostic tools

Moszyński, Rafał; Żywica, Patryk; Wójtowicz, Andrzej; Szubert, Sebastian; Sajdak, Stefan; Stachowiak, Anna; Dyczkowski, Krzysztof; Wygralak, Maciej; Szpurek, Dariusz

doi:10.17772/gp/1879

Cited by 18 publications

(8 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Other reports revealed the age group above the 65 years, constitutes 30-40 % of all ovarian cancer patients (22,54). This higher prevalence of age linked ovarian malignancy may related to menopausal period (14) and advance age (50).…”

Section: Discussionmentioning

confidence: 91%

“…The lifetime risk of developing ovarian cancer in general population is 1.4 per cent and the mean age of presentation is 64 years, even though its incidence are varied by regions (7). Many factors play major role in the disease development and these includes advance age (8,9), genetics associations (10)(11)(12), early menstruation (13), late menopause (14) and hormonal therapy (15). An ovarian tumors are mainly primary but secondaries from colon (16), stomach (17), small intestine (18), pancreas (6), breast (19) and even thyroid cancer (20) are also common.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The Response of Second Line Chemotherapy Platinum Resistant Ovarian Cancer in Sudan: 2013-2017

Alshykh

Essa

Suleiman

et al. 2019

Preprint

View full text Add to dashboard Cite

Background Ovarian carcinoma is the fifth leading cause of cancer death worldwide. The tumor mostly associated with variant factors such as advance age, early menstruation and gene association. We aimed to highlight the effectiveness of the second line chemotherapy in the management of ovarian cancer patients in Sudan.Methods The data were collected from the hospital patient’s records for five years period of time, included 62 patients with ovarian cancer who is treated by the second line platinum resistant chemotherapy.Result The peak prevalence of the patients was found in Al-Gazeera state, and the least in Al-Gadarif state. Age group above 55 years was the most affected group. The vast majority of patients showed partially mass disappearing, completes and continue growing tumor respectively. All patients received variant cycles of chemotherapy as fellow 3, 6, 2, 4, 5, 1 cycle respectively. 79.4% of the patients had achieved the normal value of cancer antigen 125 (CA125) levels after the treatment. In 50% of patients the cancer recurred after 1-2 months, 32.2% after 3-4 months and 17.8% after 5-6 months. The serous adenocarcinoma was found to be the most histological type in all the patients and the least two types were observed are cell carcinoma and serous papillary.Conclusion Our findings suggested that, Al-Gazeera state citizens were more vulnerable to resist the first line chemotherapy than others. The Sudanese patients with ovarian cancer may have better response to Gemzar.

show abstract

Section: Discussionmentioning

confidence: 91%

Section: Introductionmentioning

confidence: 99%

The Response of Second Line Chemotherapy Platinum Resistant Ovarian Cancer in Sudan: 2013-2017

Alshykh

Essa

Suleiman

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…All patients had no missing values in the attributes required by the diagnostic scales. The dataset is described in detail in [10].…”

Section: Evaluation and Results Analysismentioning

confidence: 99%

“…They vary from basic scoring systems [6] , through rule-based schemes [7] to machine learning techniques [8]. Both the sensitivity and specificity of some models exceeds 90% in external evaluation [9,10].…”

Section: Motivationmentioning

confidence: 99%

Improving medical decisions under incomplete data using interval–valued fuzzy aggregation

Żywica¹,

Wójtowicz²,

Stachowiak³

et al. 2015

Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and

Self Cite

View full text Add to dashboard Cite

We state a problem concerning how to make an effective and proper decision in the presence of data incompleteness. As an example we consider a medical diagnostic system where the problem of missing data is commonly encountered. We propose and evaluate an approach that makes it possible to reduce the influence of missing data on the final result and to improve the quality of the decision. The process involves interval-valued fuzzy set modelling, uncertaintification of classical methods, and finally aggregation of the incomplete results. It was verified that the aggregation results in meaningful and accurate decisions despite the missing data.

show abstract

“…First, we consider that when the predictive models are assessed, it seems reasonable to provide data about the level of diagnostic confidence in SA for the tumors included. In general, other studies on the efficacy of prognostic models provided detailed characteristics of US features and the clinical data on the women in the studies . Data about relative confidence levels of the SA would provide information about the clinical difficulties encountered in the diagnosis of the tumors included in the studies, thereby providing essential information about the conditions under which the predictive model was validated.…”

Section: Discussionmentioning

confidence: 99%

Performance of Selected Models for Predicting Malignancy in Ovarian Tumors in Relation to the Degree of Diagnostic Uncertainty by Subjective Assessment With Ultrasound

Szubert

Szpurek²,

Wójtowicz

et al. 2019

J of Ultrasound Medicine

Self Cite

View full text Add to dashboard Cite

Objectives-The study's main aim was to evaluate the relationship between the performance of predictive models for differential diagnoses of ovarian tumors and levels of diagnostic confidence in subjective assessment (SA) with ultrasound. The second aim was to identify the parameters that differentiate between malignant and benign tumors among tumors initially diagnosed as uncertain by SA.Methods-The study included 250 (55%) benign ovarian masses and 201 (45%) malignant tumors. According to ultrasound findings, the tumors were divided into 6 groups: certainly benign, probably benign, uncertain but benign, uncertain but malignant, probably malignant, and certainly malignant. The performance of the risk of malignancy index, International Ovarian Tumor Analysis assessment of different neoplasias in the adnexa model, and International Ovarian Tumor Analysis logistic regression model 2 was analyzed in subgroups as follows: SA-certain tumors (including certainly benign and certainly malignant) versus SA-probable tumors (probably benign and probably malignant) versus SA-uncertain tumors (uncertain but benign and uncertain but malignant).Results-We found a progressive decrease in the performance of all models in association with the increased uncertainty in SA. The areas under the receiver operating characteristic curve for the risk of malignancy index, logistic regression model 2, and assessment of different neoplasias in the adnexa model decreased between the SA-certain and SA-uncertain groups by 20%, 28%, and 20%, respectively. The presence of solid parts and a high color score were the discriminatory features between uncertain but benign and uncertain but malignant tumors.Conclusions-Studies are needed that focus on the subgroup of ovarian tumors that are difficult to classify by SA. In cases of uncertain tumors by SA, the presence of solid components or a high color score should prompt a gynecologic oncology clinic referral.

show abstract

Menopausal status strongly influences the utility of predictive models in differential diagnosis of ovarian tumors: An external validation of selected diagnostic tools

Cited by 18 publications

References 0 publications

The Response of Second Line Chemotherapy Platinum Resistant Ovarian Cancer in Sudan: 2013-2017

The Response of Second Line Chemotherapy Platinum Resistant Ovarian Cancer in Sudan: 2013-2017

Improving medical decisions under incomplete data using interval–valued fuzzy aggregation

Performance of Selected Models for Predicting Malignancy in Ovarian Tumors in Relation to the Degree of Diagnostic Uncertainty by Subjective Assessment With Ultrasound

Contact Info

Product

Resources

About