Scoring System and Management Algorithm Assessing the Role of Survivin Expression in Predicting Progressivity of HPV Infections in Precancerous Cervical Lesions

Indarti, Junita; Aziz, M. F.; Suryawati, Bethy; Fernando, Darrell

doi:10.7314/apjcp.2013.14.3.1643

Cited by 5 publications

(4 citation statements)

References 21 publications

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“…Immunohistochemistry of 81 cases of cervical cancer, 86 cases of CIN, and 35 cases of chronic cervicitis tissues revealed 0.0%, 48.8%, and 88.9% survivin expression, suggesting that survivin specifically inhibits the activity of the most downstream effective molecule Caspase-3 and apoptosis (Wand et al, 2004); these differences may be used to predict the course of intraepithelial cervical lesions. Indarti et al (2013) found that determination of survivin expression by immunocytochemistry staining, along with other significant risk factors, can be used in a scoring system to predict the progressivity of CIN lesions. Application of this scoring system may be beneficial in determining the action of therapy towards the patient.…”

Section: Discussionmentioning

confidence: 99%

MEKK3 and Survivin Expression in Cervical Cancer: Association with Clinicopathological Factors and Prognosis

Cao

Lu²,

Zhang³

et al. 2014

Asian Pacific Journal of Cancer Prevention

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Section: Discussionmentioning

confidence: 99%

MEKK3 and Survivin Expression in Cervical Cancer: Association with Clinicopathological Factors and Prognosis

Cao

Lu²,

Zhang³

et al. 2014

Asian Pacific Journal of Cancer Prevention

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“…A scoring system was developed with: (a) a ß-coefficient obtained for each significant factor from the multivariate logistical regression model; (b) each of the coefficient variables rounded off to a whole integer; and (c) the score of each variable set as its corresponding coefficient [14,15]. The cut-off values, sensitivity, and specificity of each score were determined using the receiver operating characteristic (ROC) curve method.…”

Section: Methodsmentioning

confidence: 99%

A Scoring System to Predict Arm Lymphedema Risk for Individual Chinese Breast Cancer Patients

Liu

Wang

et al. 2016

Breast Care

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Background: Lymphedema (LE) is recognized as a common complication after axillary lymph node dissection (ALND). Numerous studies have attempted to identify risk factors for LE. However, it is difficult to predict the probability of LE for an individual patient. The purpose of this study was to construct a scoring system for predicting the probability of LE after ALND for Chinese breast cancer patients. Patients and Methods: 358 breast cancer patients were surveyed and followed for 12 months. LE was defined by circumferential measurement. Univariate and multivariate logistic regression analyses were used to screen risk factors of LE. Based on this, ß-coefficient of each risk factor was translated into a prognostic score and the scoring system was constructed. The area under the receiver operating characteristic curve (AUC) and calibration were calculated as an index for the predictive value of the scoring system. The model was internally validated using bootstrapping techniques. Results: The incidence rate of LE was 31.84%. Variables associated with LE and their corresponding score in the scoring system were: the level of ALND (level I = 0, level II = 1, level III = 2), history of hypertension (yes = 1, no = 0), surgery on dominant arm (yes = 1, no = 0), radiotherapy (yes = 2, no = 0), and surgical infection/seroma/early edema (yes = 2, no = 0). The probability of LE was predicted according to the total risk scores. The system had good discrimination, with an AUC at 0.877. If a cut-off value of 3 was used, the sensitivity was 81.20% and the specificity was 80.90%. An individual whose total risk score was higher than 3 was recognized as being at risk for LE. On internal validation, the bootstrap-corrected predictive accuracy was 0.798. The model demonstrated excellent calibration in the development set and internal validation. Conclusions: Our scoring system could be a simple and easy tool for physicians to estimate the risk of LE.

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“…Survivin expression in neoplasia and oral potentially malignant disorders (OPMD) may be related to the greater malignancy potential and worst prognosis …”

Section: Introductionmentioning

confidence: 99%

Smoking cessation leads to changes in survivin expression in oral mucosa

Lima

Crastechini

Santos

et al. 2017

J Oral Pathology Medicine

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Scoring System and Management Algorithm Assessing the Role of Survivin Expression in Predicting Progressivity of HPV Infections in Precancerous Cervical Lesions

Cited by 5 publications

References 21 publications

MEKK3 and Survivin Expression in Cervical Cancer: Association with Clinicopathological Factors and Prognosis

MEKK3 and Survivin Expression in Cervical Cancer: Association with Clinicopathological Factors and Prognosis

A Scoring System to Predict Arm Lymphedema Risk for Individual Chinese Breast Cancer Patients

Smoking cessation leads to changes in survivin expression in oral mucosa

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