Latar belakang: Sebagian besar pasien kanker usia lanjut terdiagnosis pada stadium lanjut dengan peningkatan risiko mortalitas. Identifikasi faktor prediktor yang memengaruhi terjadinya mortalitas satu tahun diharapkan dapat membantu stratifikasi risiko dan menjadi pertimbangan perencanaan pelayanan kesehatan, edukasi, serta persiapan advanced care planning.Tujuan: Mengetahui faktor prediktor mortalitas satu tahun pada lansia dengan kanker padat metastasis dan mengembangkan model prediksi mortalitas satu tahun.Metode: Studi kohort retrospektif dengan menelusuri rekam medis pasien berusia ≥60 tahun dengan kanker padat metastasis berdasarkan pemeriksaan histopatologi atau radiologi yang berobat di poli onkologi RS Kanker Dharmais pada Januari 2020 hingga Desember 2021. Dilakukan analisis bivariat chi-square antara usia, jenis kelamin, ADL, ECOG-PS, jenis kanker, metastasis organ, jumlah metastasis, status nutrisi, komorbid, jumlah komorbid, polifarmasi, gangguan kognitif, gangguan mood, dan best supportive care dengan mortalitas satu tahun sesudah diagnosis kanker metastasis. Analisis multivariat dan model prediksi dilakukan dengan regresi logistik.Hasil: Terdapat 210 subjek dengan hasil analisis bivariat menunjukkan hubungan antara ECOG-PS, status nutrisi, dan pemberian best supportive care dengan mortalitas satu tahun (p<0,05). Hasil regresi logistik menunjukkan faktor prediktor independen mortalitas yaitu metastasis organ (OR 2,468 [IK 95%1,163-5,317]), status nutrisi (OR 1,943 [IK 95%1,048-3,604]), ECOG-PS (OR 2,302 [IK 95%1,241-4,271]), dan best supportive care (OR 3,157 [IK 95%1,288-7,738]). Model prediksi mortalitas satu tahun memiliki nilai AUC 0,705 (IK 95%95%: 0,629 – 0,781).Kesimpulan:Faktor prediktor independen terhadap mortalitas 1 tahun sesudah diagnosis metastasis yaitu metastasis organ, ECOG-PS, status nutrisi, dan best supportive care.

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Background: Identification of patients on their final year is important to help physicians to make personalized treatment plan according to life expectancy and to guide patients and families to prepare an advanced care planning.

Methods: We retrospectively included patients aged ≥60 years who had metastatic solid cancer and in whom geriatric assessment was performed in Dharmais National Cancer Center outpatient clinic. A total of 210 subjects were enrolled between January 2020 to December 2021. The primary analyses were performed from April to May 2023. Chi square analysis was performed between age, sex, ADL, ECOG-PS, type of cancer, visceral metastasis, number of metastatic sites, nutritional status, comorbidity, multimorbidity, polypharmacy, cognitive impairment, mood disorder, and best supportive care with one-year mortality. Variables with p value <0.25 were analysed further with logistic regression to develop a prediction model. The model’s discriminative ability was assessed with model’s area under the curve. Calibration was performed using bootstrap method.

Result: We collected 210 subjects, with median age, 66,5 years. Lung cancer was the most common malignancy (44.3%). Logistic regression results showed visceral metastasis (OR 2.468; 95% CI 1.163-5.317), nutritional status (OR 1.943; 95% CI 1.048-3.604), ECOG-PS (OR 2.302; 95% CI 1.241-4.271), and best supportive care (OR 3.157; 95% CI 1.288-7.738) were independent predictors of one year mortality. The one-year mortality prediction model has an AUC value of 0.705 (95% CI: 0.629-0.781).

Conclusion: Model developed from this study can assist clinicians to identify patients in their last year of life who need palliative care and to prepare an advance care planning.