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Purpose: The ultimate goal of cytoreduction surgery is the complete removal of all visible tumors (complete cytoreductive surgery) or tumor residues <1 cm (optimal cytoreduction surgery). Following cytoreduction surgery in ovarian cancer, tumor residue is one of the most important prognostic factors. Oncologists strive to be able to predict the outcome of cytoreduction surgery during the presurgical period. The purpose of this study was to assess CCL5 as a modality for determining whether a patient could perform optimal cytoreduction surgery or not. Materials and Methods: This was an observational, analytic, and cross-sectional study of patients with ovarian cancer who underwent surgery at the Dr. Hasan Sadikin Bandung from 2019 to 2020. All of the patients had stage I-IV disease based on the International Federation of Gynecology and Obstetrics (FIGO) score. Results: In total, 72 patients were enrolled in this study, 31 of whom underwent suboptimal cytoreduction surgery and 41 underwent optimal cytoreduction surgery. The mean serum CCL5 level at suboptimal cytoreduction was 70,920.87 ± 36,362.966, while that at optimal cytoreduction was 43,244.95 ± 21,983.887. CCL5, as a predictor of suboptimal cytoreduction surgery, had a sensitivity of 61.3%, a specificity of 68.3%, and an accuracy of 65.7% (p = 0.012). Conclusion: Preoperative CCL5 serum levels can predict suboptimal cytoreduction surgery outcomes in patients with ovarian cancer.

Objective Visual inspection of cervix after acetic acid application (VIA) has been considered an alternative to Pap smear in resource-limited settings, like Indonesia. However, VIA results mainly depend on examiner’s experience and with the lack of comprehensive training of healthcare workers, VIA accuracy keeps declining. We aimed to develop an artificial intelligence (AI)-based Android application that can automatically determine VIA results in real time and may be further developed as a health care support system in cervical cancer screening. Result A total of 199 women who underwent VIA test was studied. Images of cervix before and after VIA test were taken with smartphone, then evaluated and labelled by experienced oncologist as VIA positive or negative. Our AI model training pipeline consists of 3 steps: image pre-processing, feature extraction, and classifier development. Out of the 199 data, 134 were used as train-validation data and the remaining 65 data were used as test data. The trained AI model generated a sensitivity of 80%, specificity of 96.4%, accuracy of 93.8%, precision of 80%, and ROC/AUC of 0.85 (95% CI 0.66–1.0). The developed AI-based Android application may potentially aid cervical cancer screening, especially in low resource settings.

Tujuan: Penelitian ini bertujuan untuk mengetahui gambaran klinis dan histopatologi pasien kanker ovarium di RSHS tahun 2019-2020. Metode: Penelitian deskriptif ini dilaksanakan di RSUP Dr. Hasan Sadikin Bandung dengan menggunakan data rekam medis pasien kanker ovarium yang didiagnosis secara histopatologi tahun 2019-2020. Sampel dipilih menggunakan metode total sampling. Hasil: Penelitian ini menunjukan dari 140 pasien, mayoritas berusia 46-55 tahun (31,4%), multipara (60,7%), dan IMT normal (57,1%). Pasien mayoritas mengeluhkan adanya benjolan pada abdomen (100%) dengan karakteristik kistik sebagian padat (51,4%), berbenjol (57,1%), unilateral (87,4%), dan immobile (35,0%). Kebanyakan pasien memiliki nilai haemoglobin (75,3%) dan albumin (20,7%) rendah. Tumor marker yang paling sering ditemukan adalah CA 125 (37,9%). Mayoritas pasien didiagnosis pada stadium III (47,1%), tipe histopatologi mucinous carcinoma (20,0%) dan dilakukan operasi complete surgical staging (46,8%). Kesimpulan: Pasien kanker ovarium tahun 2019-2020 terbanyak adalah pada usia 46-55, multipara, IMT normal, mengeluhkan massa pada abdomen dengan karakteristik kistik sebagian padat, berbenjol, unilateral. Umumnya pasien mengalami penurunan nilai haemoglobin dan albumin serta berada pada stadium III dengan tipe histopatologi mucinous carcinoma dan dilakukan operasi complete surgical staging. Clinical Features and Histopathology of Ovarian Cancer at RSUP Dr. Hasan Sadikin Bandung 2019-2020 Abstract Objective: This study aimed to determine the clinical and histopathological features of ovarian cancer patients at Hasan Sadikin General Hospital Bandung 2019-2020. Method: This descriptive research was conducted at Hasan Sadikin General Hospital Bandung using medical record data for ovarian cancer patients diagnosed histopathologically in 2019-2020. The sample was selected using the total sampling method. Results: This study showed that from 140 patients, the majority were aged 46-55 years (31.4%), multiparous (60.7%), and normal BMI (57.1%). The majority of patients complained of a lump in the abdomen (100%) with the characteristics of a cyst with partially solid (51.4%), uneven surface (57.1%), unilateral (87.4%), and immobile (35.0%). Most patients had low hemoglobin (75.3%) and albumin (20.7%) values. The most common tumor marker found was CA 125 (37.9%). The majority of patients were in stage III (47.1%), the histopathological type of mucinous carcinoma (20.0%), and underwent complete surgical staging (46.8%). Conclusion: Most ovarian cancer patients in 2019-2020 were aged 46-55, multiparous, normal BMI, complained of a mass in the abdomen with the characteristics of a cyst with partially solid,uneven surface, unilateral. Generally, patients have decreased hemoglobin and albumin values were diagnosed as stage III, the histopathological type of mucinous carcinoma and underwent complete surgical staging. Key words: ovarian cancer, clinical features, histopathology