Estimating the risk of brain metastasis for patients newly diagnosed with cancer

被引:2
|
作者
Miccio, Joseph A. [1 ]
Tian, Zizhong [2 ]
Mahase, Sean S. [1 ]
Lin, Christine [1 ,3 ]
Choi, Serah [3 ]
Zacharia, Brad E. [4 ]
Sheehan, Jason P. [5 ]
Brown, Paul D. [6 ]
Trifiletti, Daniel M. [7 ]
Palmer, Joshua D. [8 ]
Wang, Ming [9 ]
Zaorsky, Nicholas G. [3 ]
机构
[1] Penn State Canc Inst, Dept Radiat Oncol, Hershey, PA USA
[2] Penn State Coll Med, Dept Publ Hlth Sci, Div Biostat & Bioinformat, Hershey, PA USA
[3] Case Western Reserve Sch Med, Univ Hosp Seidman Canc Ctr, Dept Radiat Oncol, Cleveland, OH 44106 USA
[4] Penn State Canc Inst, Dept Neurosurg, Hershey, PA USA
[5] Univ Virginia, Sch Med, Dept Neurosurg, Charlottesville, VA USA
[6] Mayo Clin, Dept Radiat Oncol, Rochester, MN USA
[7] Mayo Clin, Dept Radiat Oncol, Jacksonville, FL USA
[8] Ohio State Univ, James Comprehens Canc Ctr, Dept Radiat Oncol, Columbus, OH USA
[9] Case Western Reserve Univ, Sch Med, Dept Populat & Quantitat Hlth Sci, Cleveland, OH USA
来源
COMMUNICATIONS MEDICINE | 2024年 / 4卷 / 01期
基金
英国科研创新办公室;
关键词
GRADED PROGNOSTIC ASSESSMENT; CELL CARCINOMA; SQUAMOUS-CELL; LUNG; SURVIVAL; SURVEILLANCE;
D O I
10.1038/s43856-024-00445-7
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
BackgroundBrain metastases (BM) affect clinical management and prognosis but limited resources exist to estimate BM risk in newly diagnosed cancer patients. Additionally, guidelines for brain MRI screening are limited. We aimed to develop and validate models to predict risk of BM at diagnosis for the most common cancer types that spread to the brain.MethodsBreast cancer, melanoma, kidney cancer, colorectal cancer (CRC), small cell lung cancer (SCLC), and non-small cell lung cancer (NSCLC) data were extracted from the National Cancer Database to evaluate for the variables associated with the presence of BM at diagnosis. Multivariable logistic regression (LR) models were developed and performance was evaluated with Area Under the Receiver Operating Characteristic Curve (AUC) and random-split training and testing datasets. Nomograms and a Webtool were created for each cancer type.ResultsWe identify 4,828,305 patients from 2010-2018 (2,095,339 breast cancer, 472,611 melanoma, 407,627 kidney cancer, 627,090 CRC, 164,864 SCLC, and 1,060,774 NSCLC). The proportion of patients with BM at diagnosis is 0.3%, 1.5%, 1.3%, 0.3%, 16.0%, and 10.3% for breast cancer, melanoma, kidney cancer, CRC, SCLC, and NSCLC, respectively. The average AUC over 100 random splitting for the LR models is 0.9534 for breast cancer, 0.9420 for melanoma, 0.8785 for CRC, 0.9054 for kidney cancer, 0.7759 for NSCLC, and 0.6180 for SCLC.ConclusionsWe develop accurate models that predict the BM risk at diagnosis for multiple cancer types. The nomograms and Webtool may aid clinicians in considering brain MRI at the time of initial cancer diagnosis. Miccio et al. utilize the US National Cancer Database (NCDB) to develop models to estimate the risk of brain metastasis for newly-diagnosed cancers. They provide nomograms and a web tool for risk estimation across multiple cancer types. When patients are diagnosed with cancer, it is unknown which patients have a significant risk of cancer spread to the brain. Cancer spread to the brain is important to diagnose since it changes how patients are treated and affects their prognosis. This study used a large national database of patients diagnosed with cancer and studied the characteristics that were associated with cancer spread to the brain. The results can be used by doctors to assess the risk of cancer spread to the brain and determine which patients with cancer may benefit most from brain imaging.
引用
收藏
页数:12
相关论文
共 50 条
  • [1] Initial Approach to Patients with a Newly Diagnosed Solitary Brain Metastasis
    Liu, James K. C.
    NEUROSURGERY CLINICS OF NORTH AMERICA, 2020, 31 (04) : 489 - 503
  • [2] Frequency of Hepatic Metastasis in newly diagnosed patients of Breast Cancer by Computed Tomography
    Tamkeen, Naila
    Ahmed, Adnan
    Aman, Sadia
    Rokhan, Bakht
    Iqbal, Majid
    Ahmad, Abbas
    PAKISTAN JOURNAL OF MEDICAL & HEALTH SCIENCES, 2020, 14 (04): : 1358 - 1360
  • [3] Predictive models for the risk and prognosis of bone metastasis in patients with newly-diagnosed esophageal cancer: A retrospective cohort study
    Yuan, Bei
    Lu, Haojie
    Hu, Dong
    Xu, Kai
    Xiao, Songhua
    FRONTIERS IN SURGERY, 2023, 9
  • [4] Comparative analysis of survival, treatment, cost and resource use among patients newly diagnosed with brain metastasis by initial primary cancer
    Ray, Saurabh
    Dacosta-Byfield, Stacey
    Ganguli, Arijit
    Bonthapally, Vijayveer
    Teitelbaum, April
    JOURNAL OF NEURO-ONCOLOGY, 2013, 114 (01) : 117 - 125
  • [5] Comparative analysis of survival, treatment, cost and resource use among patients newly diagnosed with brain metastasis by initial primary cancer
    Saurabh Ray
    Stacey Dacosta-Byfield
    Arijit Ganguli
    Vijayveer Bonthapally
    April Teitelbaum
    Journal of Neuro-Oncology, 2013, 114 : 117 - 125
  • [6] Impact of sites versus number of metastases on survival of patients with organ metastasis from newly diagnosed cervical cancer
    Yin, Zhuomin
    Tang, Huarong
    Li, Li
    Ni, Juan
    Yuan, Shuhui
    Lou, Hanmei
    Chen, Ming
    CANCER MANAGEMENT AND RESEARCH, 2019, 11 : 7759 - 7766
  • [7] Prevalence, etiology and risk factors of anemia in patients with newly diagnosed cancer
    Kenar, Gokce
    Koksoy, Elif Berna
    Urun, Yuksel
    Utkan, Gungor
    SUPPORTIVE CARE IN CANCER, 2020, 28 (11) : 5235 - 5242
  • [8] Risk factors and predictors of lymph nodes metastasis and distant metastasis in newly diagnosed T1 colorectal cancer
    Guo, Kaibo
    Feng, Yuqian
    Yuan, Li
    Wasan, Harpreet S.
    Sun, Leitao
    Shen, Minhe
    Ruan, Shanming
    CANCER MEDICINE, 2020, 9 (14): : 5095 - 5113
  • [9] Brain metastases in newly diagnosed lung cancer: epidemiology and conditional survival
    Yuan, Chong
    Zheng, Huandong
    TRANSLATIONAL CANCER RESEARCH, 2024, 13 (10) : 5417 - 5428
  • [10] Survival of patients newly diagnosed with colorectal cancer and with a history of previous cancer
    Pruitt, Sandi L.
    Gerber, David E.
    Zhu, Hong
    Heitjan, Daniel F.
    Maddineni, Bhumika
    Xiong, Danyi
    Singal, Amit G.
    Tavakkoli, Anna
    Halm, Ethan A.
    Murphy, Caitlin C.
    CANCER MEDICINE, 2021, 10 (14): : 4752 - 4767