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Di Indonesia kanker payudara merupakan kanker tertinggi yang banyak datang pada stadium lanjut sehingga berdampak terhadap mortalitas dan tingginya pembiayaan. Mammografi merupakan alat skrining dan diagnosis yang sudah terbukti efektifitasnya menghasilkan “down staging” pada negara maju, Indonesia sebagai negara berkembang belum menjadikan skrining mammografi sebagai program nasional. Dilakukan studi parsial evaluasi ekonomi biaya dan luaran dengan membandingkan mammografi untuk skrining berbasis populasi terhadap oportunistik skrining di RS. Dilakukan uji coba skrining berbasis populasi terhadap 683 wanita dengan menggunakan mobil mammografi hingga didapatkan case detected serta diambil data retrospektif pasien deteksi dini dengan mammografi hingga penegakan diagnosis di RS dalam periode satu tahun. Dilakukan analisis biaya berdasarkan perspektif program dengan analisis luaran case detected. Didapatkan unit cost pemeriksaan skrining adalah Rp871,045. dengan case detected 0,4% dan cost per case detected Rp Rp290,348,509. Pada deteksi dini di RS didapakan unit cost Rp1,137,881 dan 3% kasus positif kanker. Terhadap skrining berbasis populasi, untuk mendapatkan satu kasus positif kanker diperlukan biaya sebesar Rp 262.342.333. Dengan sumber daya yang dimiliki perlu dilakukan inovasi dalam deteksi dini mammografi melalui penguatan pelaksanaan skrining CBE sebagai program nasional didukung pendekatan akses melalui diagnosis dini dengan mobil mammografi terutama di daerah rentan sehingga dihasilkan diagnosis secara cepat dan tepat dan biaya yang murah. Diperlukan peran pemerintah melalui pembiayaan yang berkelanjutan terhadap deteksi dini mammografi untuk dapat menurunkan angka mortalitas dan pembiyaan dalam pengobatan kanker. Kata kunci: Kanker payudara, mammografi, cost and outcome.
Breast cancer is the highest cancer in Indonesia that come at late stage so have impact on mortality and high funding. Mammography is a screening and diagnosis that has proven its effectiveness in producing "down staging" in developed countries, Indonesia as a developing country has not made mammography screening a national program. A partial study of economic evaluation of costs and outcomes was conducted by comparing mammography for population-based screening to opportunistic screening in hospitals. A population-based screening was conducted on 683 women using a mobile mammography until a case was detected and retrospective data taken from early detection patients with mammography to diagnose the hospital in a period of one year. A cost analysis is carried out based on the program perspective with a case detected output analysis. The unit cost of screening is Rp.871,045. with case detected 0.4% and cost per case detected Rp.290,348,509. At early detection in the hospital unit unit costs are obtained Rp1,137,881 and 3% of positive cases of cancer. For population-based screening, to get one positive case of cancer costs Rp 262,342,333. With the available resources, innovation in the early detection of mammography needs to be done through strengthening the implementation of CBE screening as a national program supported by an access approach through early diagnosis by mammography cars, especially in vulnerable areas so that diagnosis is produced quickly and accurately and at a low cost. The role of government is needed through ongoing financing of early detection of mammography to be able to reduce mortality and financing in the treatment of cancer. Keywords: Breast cancer, mammography, cost and outcome
ABSTRAK
Latar Belakang: Kanker payudara merupakan jenis kanker dengan insidensi tertinggi di Indonesia, dengan sebagian besar pasien terdiagnosis pada stadium lanjut salah satunya karena keterlambatan diagnosis di fasilitas kesehatan primer. Rendahnya kemampuan dokter umum dalam menegakkan diagnosis klinis kanker payudara serta alur rujukan yang panjang juga berkontribusi memperberat keterlambatan tersebut. Tujuan: Menghasilkan model prediksi diagnosis klinis kanker payudara di pelayanan kesehatan primer menggunakan skor malignansi “Probability of Breast Cancer (BOBAN)” Metode: Studi ini menggunakan mixed method, dengan pendekatan desain explanatory sequential, penelitian kuantitatif menggunakan desain potong lintang dilanjutkan penelitian kualitatif dengan desain studi kasus. Penelitian ini melibatkan 1.169 wanita usia ≥30 tahun yang melakukan deteksi dini di RS Kanker Dharmais (2020–2022). Variabel prediktor dianalisis dengan uji multivariat regresi logistik untuk penyusunan model skoring. Tahap kedua berupa uji akurasi (sensitivitas-spesifisitas) dan nilai probabilitas prediksi. Tahap ketiga berupa uji kualitatif melalui diskusi kelompok terfokus (FGD) dengan dokter umum di puskesmas. Hasil: Model prediksi terdiri dari tujuh variabel terpilih, yaitu usia, riwayat keluarga tingkat I, riwayat melahirkan, riwayat menyusui, benjolan payudara, kelenjar getah bening aksila, dan gejala lanjut kanker. Model ini memiliki nilai kalibrasi yang baik (p-value 0.826) dan nilai AUC pada ROC sebesar 0,920 (CI 95% 0,892 - 0,947; p-value 0,00) menunjukkan diskriminasi yang sangat baik. Total skor antara 0–177, dengan titik potong optimal pada skor 69 (sensitivitas 86,7%, spesifisitas 82,9%, dan nilai probabilitas 10,45%). Skor rendah (0-68) didiagnosis bukan kanker payudara dan skor tinggi (69-177) didiagnosis curiga kanker payudara. Evaluasi kualitatif menunjukkan bahwa skor malignansi BOBAN dapat diaplikasikan oleh dokter umum di fasilitas kesehatan pelayanan primer. Kesimpulan: Skor malignansi ini dapat memprediksi diagnosis klinis dan menghitung nilai probabilitas kanker payudara. Skor malignansi BOBAN direkomendasikan untuk digunakan sebagai instrumen deteksi dini kanker payudara di faskes primer dan dapat menjadi solusi bagi dokter umum untuk mempemudah skrining rujukan tatalaksana kanker payudara di Indonesia.
ABSTRACT
Background: Breast cancer is the most prevalent type of cancer in Indonesia, with the majority of patients diagnosed at an advanced stage, partly due to delayed diagnosis in primary healthcare settings. Limited diagnostic capabilities among general practitioners and lengthy referral processes contribute significantly to these delays. Objective: To develop a clinical prediction model for breast cancer diagnosis in primary healthcare using the "Probability of Breast Cancer (BOBAN)" malignancy score. Methods: This study employed a mixed-method approach, consisting of a quantitative cross-sectional study followed by a qualitative explanatory sequential design. A total of 1,169 women aged ≥30 years who underwent early detection at Dharmais Cancer Hospital (2020–2022) were included. Predictor variables were analyzed using multivariate logistic regression to construct the scoring model. The second phase involved evaluating the model’s diagnostic accuracy (sensitivity-specificity) and predictive probability values. The third phase included qualitative assessment through focus group discussions (FGDs) with general practitioners at community health centers (puskesmas). Results: The prediction model comprised seven selected variables: age, first-degree family history of breast cancer, childbirth history, breastfeeding history, presence of a breast lump, axillary lymph nodes, and advanced cancer symptoms. The model demonstrated good calibration (p-value = 0.826) and excellent discrimination with an AUC of 0.920 (95% CI: 0.892–0.947; p-value < 0.001). The total score ranged from 0–177, with an optimal cutoff score of 69 (sensitivity 86.7%, specificity 82.9%, predictive probability 10.45%). A low score (0–68) indicated a non-breast cancer diagnosis, while a high score (69–177) indicated suspected breast cancer. Qualitative evaluation indicated that the BOBAN malignancy score is feasible for implementation by general practitioners in primary care settings. Conclusion: The malignancy score is capable of predicting clinical diagnosis and estimating the probability of breast cancer. The BOBAN score is recommended as a screening tool for early detection in primary healthcare facilities and offers a practical solution for general practitioners to facilitate breast cancer management referrals in Indonesia.