Ahmed Anwar E, Alzahrani Faris S, Gharawi Ahmed M, Alammary Salman A, Almijmaj Fahad H, Alhusayni Fahad M, McClish Donna K, Al-Jahdali Hamdan, Olayan Ashwaq A Al, Jazieh Abdul Rahman
King Abdullah International Medical Research Center (KAIMRC), Riyadh, Saudi Arabia,
King Saud Bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia,
Cancer Manag Res. 2018 Oct 25;10:4981-4986. doi: 10.2147/CMAR.S173666. eCollection 2018.
Imaging tests used in our center are usually inadequate to confirm the high risk for pancreatic cancer. We aimed to use a combination of potential predictors including imaging tests to quantify the risk of pancreatic cancer and evaluate its utility.
This was a retrospective cohort study of patients who were suspected as having pancreatic cancer and underwent biopsy examination of pancreatic mass at King Abdulaziz Medical City, Riyadh, Saudi Arabia, between January 1, 2013, and December 31, 2016. We retrieved data on demographics, clinical history, imaging tests, and final pancreatic diagnosis from medical records.
Of the 206 who underwent pancreatic biopsies, the mean age was 63.6 years; 54.4% were male. Of all the biopsies, 57.8% were malignant and 42.2% were benign masses. Nine factors contributed significantly to the risk of pancreatic cancer and were noted: older age (adjusted odds ratio [aOR] =1.048; =0.010), male gender (aOR =4.670; =0.008), weight loss (aOR =14.810; =0.001), abdominal pain (aOR =7.053; =0.0.001), blood clots (aOR =20.787; =0.014), pancreatitis (aOR =4.473; =0.021), jaundice (aOR =7.446; =0.003), persistent fatigue (aOR =22.015; =0.015), and abnormal imaging tests (aOR =67.124; =0.001). The model yielded powerful calibration (=0.953), excellent predictive utility (area under the receiver operating characteristic curve 96.3%; 95% CI =94.1, 98.6), with optimism-corrected area under the curve bootstrap resampling of 94.9%. An optimal cut-off risk probability of 0.513 yielded a sensitivity of 94% and specificity of 84.7% for risk classification.
The study developed and validated a risk model for quantifying the risk of pancreatic cancer. Nine characteristics were associated with increased risk of pancreatic cancer. This risk assessment model is feasible and highly sensitive and could be useful to improve screening performance and the decision-making process in clinical settings in Saudi Arabia.
我们中心使用的影像学检查通常不足以确诊胰腺癌的高风险。我们旨在结合包括影像学检查在内的潜在预测指标来量化胰腺癌风险并评估其效用。
这是一项回顾性队列研究,研究对象为2013年1月1日至2016年12月31日期间在沙特阿拉伯利雅得阿卜杜勒阿齐兹国王医疗城疑似患有胰腺癌并接受胰腺肿块活检检查的患者。我们从病历中检索了人口统计学、临床病史、影像学检查及最终胰腺诊断的数据。
在接受胰腺活检的206例患者中,平均年龄为63.6岁;54.4%为男性。在所有活检病例中,57.8%为恶性,42.2%为良性肿块。有9个因素对胰腺癌风险有显著影响,具体如下:年龄较大(调整优势比[aOR]=1.048;P=0.010)、男性(aOR=4.670;P=0.008)、体重减轻(aOR=14.810;P=0.001)、腹痛(aOR=7.053;P=0.001)、血栓(aOR=20.787;P=0.014)、胰腺炎(aOR=4.473;P=0.021)、黄疸(aOR=7.446;P=0.003)、持续疲劳(aOR=22.015;P=0.015)及影像学检查异常(aOR=67.124;P=0.001)。该模型具有强大的校准能力(P=0.953)、出色的预测效用(受试者工作特征曲线下面积为96.3%;95%可信区间=94.1,98.6),经乐观校正的曲线下面积自抽样法为94.9%。风险概率的最佳截断值为0.513,风险分类的灵敏度为94%,特异度为84.7%。
本研究开发并验证了一种用于量化胰腺癌风险的风险模型。九个特征与胰腺癌风险增加相关。这种风险评估模型可行且高度敏感,可能有助于提高沙特阿拉伯临床环境中的筛查性能和决策过程。