Malignite Risk İndeksi 1, 2, 3 Ve 4’ ün Adneksiyel Kitlelerin Benign-Malign Ayrımındaki Etkinliğinin Karşılaştırılması ve Vücut Kitle İndeksi İle Paritenin Prediktif Faktör Olarak Malignite Risk İndeksine Eklenmesinin Değerlendirilmesi

Year 2023, , 38 - 46, 20.02.2023

Eda Ozden Tokalıoglu , Abdurrahman Alp Tokalıoglu , Ömer Lütfi Tapısız

https://doi.org/10.52827/hititmedj.1240946

Abstract

Amaç: Çalışmamızın amacı; 1) Adneksiyel kitlelerin preoperatif olarak benign- malign ayrımında kullanılan malignite risk indeksi (RMI) 1-2-3 ve 4’ün duyarlılık, özgüllük, pozitif öngörme ve negatif öngörme değerlerinin birbirleriyle kıyaslanması; 2) RMI 1,2,3,4 için daha önceki çalışmalarda belirlenmiş cut-off değerlerinin bizim hasta popülasyonumuzdaki duyarlılık, özgüllük, pozitif öngörme ve negatif öngörmesinin belirlenmesi; 3) RMI ülkemize modifiye edildiğinde, en iyi duyarlılık ve özgüllüğü yakalayan cut-off değerin ROC eğrisi kullanılarak belirlenmesi; 4) Over kanserinde risk faktörü oldukları çalışmalarla kanıtlanmış obezite ve düşük pariteyi ayrı ayrı ve beraber RMI modellerine birer prediktif faktör olarak ekleyip, malign- benign ayrımında duyarlılık ve özgüllüğü ne yönde değiştirdiklerinin belirlenmesidir.
Gereç ve yöntem: Çalışmamıza Ocak 2012- Ocak 2017 tarihleri arasında adneksiyel kitle ön tanısıyla opere edilen, ultrasonografi ve CA-125 ölçümleri hastanemizde yapılan 590 hasta dahil edilmiştir. Hastaların demografik bilgileri, vücut kitle indeksi ve parite değerleri, ultrasonografi ve CA-125 ölçümleri retrospektif olarak elde edilmiştir. Her hasta için RMI 1-2-3-4; parite skorunun eklendiği RMIP 1-2-3-4, vücut kitle indeksi skorunun eklendiği RMIB 1-2-3-4 ve parite ve vücut kitle indeksinin beraber eklendiği RMIBP 1-2-3-4 hesaplanmıştır. Her hastanın operasyon sonrası patoloji sonucuyla malignite risk indeksi skorları karşılaştırılmıştır.
Bulgular: Duyarlılık ve özgüllük sırasıyla RMI-1 için %75.9- %96.9; RMI-2 için %80.3- %95.6; RMI-3 için %80.3- %94.9; RMI-4 içinse %70.8- %97.1 bulunmuştur. RMI 3 için en iyi duyarlılık ve özgüllüğü veren cut-off değeri 160.5, RMI-4 için 201.5 olarak bulunmuştur.
RMIB-1, RMIB-2, RMIB-3 ve RMIB-4; RMI-1, RMI-2, RMI-3 ve RMI-4 ile karşılaştırıldığında, testin duyarlılığının arttığı fakat özgüllüğünün artmadığı gözlenmiştir. RMIP-1, RMIP-2, RMIP-3 ve RMIP-4; RMI-1, RMI-2, RMI-3 ve RMI-4 ile karşılaştırıldığında, RMIP 1,2,3 için testin duyarlılığının azaldığı fakat özgüllüğünün hafif arttığı; RMIP-4 içinse duyarlılığın arttığı ve özgüllüğün azaldığı gözlenmiştir. Vücut kitle indeksi ve parite skorları beraberce RMI’ya ekleniğinde, RMIBP 1,2 3 ve 4’ te duyarlılık artarken özgüllüğün artmadığı gözlenmiştir.

Sonuç: RMI 1,2,3, ve 4’ ün adneksiyel kitlelerin benign- malign ayrımında etkili olduğu çalışmamızca desteklendi. Bizim çalışmamızda RMI skorlarının hepsi yüksek prediktivite göstermiş olmasına rağmen, en iyi prediktivite değerlerine RMI-2 ve RMI-3’ te ulaşıldı. Daha önce birçok çalışmayla over kanseri için risk faktörü oldukları kanıtlanan, yüksek vücut kitle indeksi ve azalmış paritenin RMI’ya eklenmesinin, indeksin duyarlılığını arttırdığını fakat özgüllüğünde olumlu bir etki yapmadığını saptadık.

Keywords

CA-125, obesity, ovarian cancer, parity, risk of malignancy index, ultrasonography

Comparison of the Efficiency of Malignancy Risk Index 1, 2, 3, and 4 in Differentiating Benign-Malignant Adnexal Masses and Evaluation of Adding Body Mass Index and Parity to the Malignancy Risk Index as a Predictive Factor

Abstract

Objective
The aims of our work are as follows; 1) Comparison of the sensitivity, specificity, positive predictive and negative predictive values of the malignancy risk index (RMI) 1-2-3 and 4, which are used in the preoperative differentiation of adnexal masses from benign to malignant; 2) Determination of sensitivity, specificity, positive predictive and negative predictive value for RMI 1,2,3,4 in our patient population of cut-off values determined in previous studies; 3) When the RMI is modified for our country, determining the cut-off value with the best sensitivity and specificity using the ROC curve; 4) To adjust the sensitivity and specificity by adding body mass index (BMI) and low parity, which have been proven by studies to be risk factors in ovarian cancer, separately and together as predictive factors to the RMI models.
Material and Method
Our study included 590 patients who were operated with a diagnosis of adnexal mass between January 2012 and January 2017 in our hospital. Demographic information, BMI and parity values, ultrasonography and CA-125 measurements of the patients were obtained retrospectively. For each patient RMI 1-2-3-4; RMIP 1-2-3-4 with parity score added, RMIB 1-2-3-4 with body mass index score added, and RMIBP 1-2-3-4 with parity and BMI added together were calculated. The postoperative pathology results of each patient were compared with the malignancy risk index scores.
Results
Sensitivity and specificity were 75.9%-96.9% for RMI-1; 80.3%- 95.6% for RMI-2; 80.3%-94.9% for RMI-3; 70.8%-97.1% for RMI-4 respectively. The cut-off value, which gives the best sensitivity and specificity was 160.5 for RMI 3 and 201.5 for RMI-4.
When compared with RMI-1, RMI-2, RMI-3 and RMI-4; RMIB-1, RMIB-2, RMIB-3 and RMIB-4, it was observed that the sensitivity of the test increased but the specificity did not. RMIP-1, RMIP-2, RMIP-3 and RMIP-4; Compared to RMI-1, RMI-2, RMI-3 and RMI-4, the sensitivity of the test for RMIP 1,2,3 decreased but the specificity slightly increased; for RMIP-4, the sensitivity increased and the specificity decreased. When BMI and parity scores were added to RMI together, sensitivity increased in RMIBP 1,2,3 and 4, specificity did not.
Conclusion
It was supported by our study that RMI 1,2,3, and 4 were effective in the differentiation of benign and malignant adnexal masses. Although all of the RMI scores showed high predictivity in our study, the best predictive values were achieved with RMI-2 and RMI-3. We found that adding high body mass index and decreased parity to RMI, which have been proven to be risk factors for ovarian cancer in many studies, increases the sensitivity of the index but does not have a positive effect on its specificity.

Keywords

CA-125, obesity, ovarian cancer, parity, risk of malignancy index, ultrasonography

References

• Sassone AM, Timor-Tritsch IE, Artner A., Westhoff C, Warren WB. Transvaginal sonographic characterization of ovarian disease: evaluation of a new scoring system to predict ovarian malignancy. Obstetrics & Gynecology 1991;78:70-76.
• Young RC., Decker DG., Wharton JT, et al. Staging laparotomy in early ovarian cancer. Jama. 1983;250:3072-3076.
• Niloff JM., Bast Jr RC, Schaetzl EM, Knapp RC. Predictive value of CA 125 antigen levels in second-look procedures for ovarian cancer. American journal of obstetrics and gynecology 1985;151: 981-986.
• Bast Jr RC, Klug, TL, John ES, et al. A radioimmunoassay using a monoclonal antibody to monitor the course of epithelial ovarian cancer. New England Journal of Medicine, 1983;309:883-887.
• Jacobs I, Bast RC. The CA 125 tumour-associated antigen: a review of the literature. Human Reproduction, 1989;4:1-12.
• Schutter EM, Kenemans P, Sohn C, et al. Diagnostic value of pelvic examination, ultrasound, and serum CA 125 in postmenopausal women with a pelvic mass. An international multicenter study. Cancer 1994;74:1398-1406.
• Jacobs I, Oram D, Fairbanks J, Turner J, Frost C, Grudzinskas JG. A risk of malignancy index incorporating CA 125, ultrasound and menopausal status for the accurate preoperative diagnosis of ovarian cancer. BJOG: An International Journal of Obstetrics & Gynaecology, 1990;97:922-929.
• Tingulstad S, Hagen B, Skjeldestad FE, Onsrud M, Kiserud T, Halvorsen T. Evaluation of a risk of malignancy index based on serum CA125, ultrasound findings and menopausal status in the pre‐operative diagnosis of pelvic masses. BJOG: An International Journal of Obstetrics & Gynaecology, 1996;103:826-831.
• Tingulstad S, Hagen B, Skjeldestad FE, Halvorsen T, Nustad K, Onsrud M. The risk-of-malignancy index to evaluate potential ovarian cancers in local hospitals. Obstetrics & Gynecology 1999;93:448-452.
• Yamamoto Y, Yamada R, Oguri H, Maeda N, Fukaya T. Comparison of four malignancy risk indices in the preoperative evaluation of patients with pelvic masses. European Journal of Obstetrics & Gynecology and Reproductive Biology. 2009;144:163-167.
• Tsilidis KK, Allen NE, Key TJ, Dossus L, Lukanova A, Bakken K. Oral contraceptive use and reproductive factors and risk of ovarian cancer in the European Prospective Investigation into Cancer and Nutrition. British journal of cancer 2011;105:1436-1442.
• Obesity: preventing and managing the global epidemic. 2000: World Health Organization.
• Aktürk E, Karaca RE, Alanbay İ, et al. Comparison of four malignancy risk indices in the detection of malignant ovarian masses. Journal of gynecologic oncology, 2011;22:177-182.
• Zheng H, Kavanagh JJ, Hu W, Liao Q, Fu S. Hormonal therapy in ovarian cancer. International journal of gynecological cancer 2007;17:325-338.
• Hanna L, Adams M. Prevention of ovarian cancer. Best Practice & Research Clinical Obstetrics & Gynaecology 2006;20:339-362.
• Pi-Sunyer FX, Becker DM, Bouchard C, et al.Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults. American Journal of Clinical Nutrition 1998;68:899-917.
• Olsen CM, Green AC, Whiteman DC, Sadeghi S, Kolahdooz F, Webb PM. Obesity and the risk of epithelial ovarian cancer: a systematic review and meta-analysis. European Journal of Cancer 2007;43:690-709.
• Di Masi A, Leboffe L, De Marinis E, et al. Retinoic acid receptors: from molecular mechanisms to cancer therapy. Molecular aspects of medicine 2015;41:1-115.
• Xie J, Poole EM, Terry KL, et al. A prospective cohort study of dietary indices and incidence of epithelial ovarian cancer. Journal of ovarian research 2014;7:112.
• Geomini P, Kruitwagen R, Bremer GL, Cnossen J, Mol BW. The accuracy of risk scores in predicting ovarian malignancy: a systematic review. Obstetrics & Gynecology 2009;113:384-394.
• Meray O, Türkçüoğlu I, Meydanlı MM, Kafkaslı A. Risk of malignancy index is not sensitive in detecting non-epithelial ovarian cancer and borderline ovarian tumor. Journal of the Turkish German Gynecological Association 2010;11:22-26.
• Bandiera E, Romani C, Specchia C, et al. Serum human epididymis protein 4 (HE4) and Risk for Ovarian Malignancy Algorithm (ROMA) as new diagnostic and prognostic tools for epithelial ovarian cancer management. Cancer Epidemiology and Prevention Biomarkers 2011;20:2496-2506.
• Bast RC, Skates S, Lokshin A, Moore RG. Differential diagnosis of a pelvic mass: improved algorithms and novel biomarkers. International Journal of Gynecological Cancer, 2012;22:S1.
• Timmerman D, Valentin L, Bourne TH, Collins WP, Verrelst H, Vergote I. Terms, definitions and measurements to describe the sonographic features of adnexal tumors: a consensus opinion from the International Ovarian Tumor Analysis (IOTA) Group. Ultrasound in Obstetrics and Gynecology 2000;16:500-505.
• Moore RG, Jabre-Raughley M, Brown AK, Robison KM, Miller M.C., Allard, W. J Comparison of a novel multiple marker assay vs the Risk of Malignancy Index for the prediction of epithelial ovarian cancer in patients with a pelvic mass. American journal of obstetrics and gynecology, 2010;203:228.
• Valentin L, Ameye L, Jurkovic D, Metzger U, Lécuru F, Van Huffel S. Which extrauterine pelvic masses are difficult to correctly classify as benign or malignant on the basis of ultrasound findings and is there a way of making a correct diagnosis? Ultrasound in obstetrics & gynecology 2006;27:438-444.
• Gadducci A, Guerrieri ME, Genazzani AR. Fertility drug use and risk of ovarian tumors: a debated clinical challenge. Gynecological Endocrinology 2013;29:30-35.
• Vessey M, Yeates D. Oral contraceptive use and cancer: final report from the Oxford–Family Planning Association contraceptive study. Contraception 2013;88:678-683.
• Schorge J, Schaffer J, Halvorson L. Pelvik Kitle. Williams Jinekoloji. Vol. 2. 2015. 246-80.
• Khan MMH, Khan A, Nojima M, et al. Ovarian cancer mortality among women aged 40-79 years in relation to reproductive factors and body mass index: latest evidence from the Japan Collaborative Cohort study. Journal of gynecologic oncology 2013;24:249-257.
• Pasalich M, Su D, Binns CW, Lee AH. Reproductive factors for ovarian cancer in southern Chinese women. Journal of gynecologic oncology 2013;24:135-140.
• Purdie DM, Bain CJ, Webb PM, Whiteman DC, Pirozzo S, Green AC. Body size and ovarian cancer: case–control study and systematic review (Australia). Cancer Causes and Control 2001;12:855-863.
• Simsek HS, Tokmak A, Ozgu E, Doganay M, Danisman N, Erkaya S. Role of a risk of malignancy index in clinical approaches to adnexal masses. Asian Pac J Cancer Prev, 2014;15:7793-7797.
• Yavuzcan A, Caglar M, Ozgu E, Ustun Y, Dilbaz S, Ozdemir I. Should cut-off values of the risk of malignancy index be changed for evaluation of adnexal masses in Asian and Pacific populations? Asian Pacific Journal of Cancer Prevention 2013;14:5455-5459.
• van den Akker PA, Aalders AL, Snijders MP, et al. Evaluation of the Risk of Malignancy Index in daily clinical management of adnexal masses. Gynecologic oncology 2010;116:384-388.
• Bailey J, Tailor A, Naik R, et al. Risk of malignancy index for referral of ovarian cancer cases to a tertiary center: does it identify the correct cases? International Journal of Gynecological Cancer 2006;16:30-34.