Hepatocellular carcinoma (HCC) has a poor prognosis, and alpha-fetoprotein (AFP) is widely used to evaluate HCC. However, the proportion of AFP-negative individuals cannot be disregarded. This study aimed to establish a nomogram of risk factors affecting the prognosis of patients with AFP-negative HCC and to evaluate its diagnostic efficiency. Data from patients with AFP-negative initial diagnosis of HCC (ANHC) between 2004 and 2015 were collected from the Surveillance, Epidemiology, and End Results database for model establishment and validation. We randomly divided overall cohort into the training or validation cohort (7:3). Univariate and multivariate Cox regression analysis were used to identify the risk factors. We constructed nomograms with overall survival (OS) and cancer-specific survival (CSS) as clinical endpoint events and constructed survival analysis by using Kaplan-Meier curve. Also, we conducted internal validation with Receiver Operating Characteristic (ROC) analysis and Decision curve analysis (DCA) to validate the clinical value of the model. This study included 1811 patients (1409 men; 64.7% were Caucasian; the average age was 64 years; 60.7% were married). In the multivariate analysis, the independent risk factors affecting prognosis were age, ethnicity, year of diagnosis, tumor size, tumor grade, surgery, chemotherapy, and radiotherapy. The nomogram-based model related C-indexes were 0.762 (95% confidence interval (CI): 0.752–0.772) and 0.752 (95% CI: 0.740–0.769) for predicting OS, and 0.785 (95% CI: 0.774–0.795) and 0.779 (95% CI: 0.762–0.795) for predicting CSS. The nomogram model showed that the predicted death was consistent with the actual value. The ROC analysis and DCA showed that the nomogram had good clinical value compared with TNM staging. The age(HR:1.012, 95% CI: 1.006–1.018, P-value < 0.001), ethnicity(African-American: HR:0.946, 95% CI: 0.783–1.212, P-value: 0.66; Others: HR:0.737, 95% CI: 0.613–0.887, P-value: 0.001), tumor diameter(HR:1.006, 95% CI: 1.004–1.008, P-value < 0.001), year of diagnosis (HR:0.852, 95% CI: 0.729–0.997, P-value: 0.046), tumor grade(Grade 2: HR:1.124, 95% CI: 0.953–1.326, P-value: 0.164; Grade 3: HR:1.984, 95% CI: 1.574–2.501, P-value < 0.001; Grade 4: HR:2.119, 95% CI: 1.115–4.027, P-value: 0.022), surgery(Liver Resection: HR:0.193, 95% CI: 0.160–0.234, P-value < 0.001; Liver Transplant: HR:0.102, 95% CI: 0.072–0.145, P-value < 0.001), chemotherapy(HR:0.561, 95% CI: 0.471–0.668, P-value < 0.001), and radiotherapy(HR:0.641, 95% CI: 0.463–0.887, P-value:0.007) were independent prognostic factors for patients with ANHC. We developed a nomogram model for predicting the OS and CSS of patients with ANHC, with a good predictive performance.

中文翻译：

---

AFP 阴性肝细胞癌患者的生存预测和预后因素分析：一项基于人群的研究

肝细胞癌（HCC）预后较差，甲胎蛋白（AFP）广泛用于评估HCC。然而，AFP 阴性个体的比例不容忽视。本研究旨在建立影响AFP阴性HCC患者预后的危险因素列线图并评估其诊断效率。从监测、流行病学和最终结果数据库收集 2004 年至 2015 年间 AFP 阴性初次诊断的 HCC (ANHC) 患者的数据，用于模型建立和验证。我们将整个队列随机分为训练队列或验证队列 (7:3)。使用单变量和多变量Cox回归分析来确定危险因素。我们构建了以总生存期（OS）和癌症特异性生存期（CSS）作为临床终点事件的列线图，并使用 Kaplan-Meier 曲线构建了生存分析。此外，我们还通过受试者操作特征（ROC）分析和决策曲线分析（DCA）进行内部验证，以验证模型的临床价值。这项研究包括 1811 名患者（1409 名男性；64.7% 为白人；平均年龄为 64 岁；60.7% 已婚）。多因素分析显示，影响预后的独立危险因素为年龄、种族、诊断年份、肿瘤大小、肿瘤分级、手术、化疗和放疗。基于列线图的模型相关 C 指数用于预测 OS 时为 0.762（95% 置信区间 (CI)：0.752–0.772）和 0.752（95% CI：0.740–0.769），预测 OS 时为 0.785（95% CI：0.774–0.795）预测 CSS 的值为 0.779 (95% CI: 0.762–0.795)。列线图模型显示预测死亡值与实际值一致。ROC分析和DCA显示列线图与TNM分期相比具有良好的临床价值。年龄（HR：1.012，95％CI：1.006–1.018，P值<0.001），种族（非裔美国人：HR：0.946，95％CI：0.783–1.212，P值：0.66；其他：HR： 0.737，95% CI：0.613–0.887，P 值：0.001），肿瘤直径（HR：1.006，95% CI：1.004–1.008，P 值 < 0.001），诊断年份（HR：0.852，95% CI ：0.729–0.997，P值：0.046），肿瘤分级（2级：HR：1.124，95％CI：0.953–1.326，P值：0.164；3级：HR：1.984，95％CI：1.574–2.501 ，P 值 < 0.001；4 级：HR：2.119，95% CI：1.115–4.027，P 值：0.022），手术（肝切除：HR：0.193，95% CI：0.160–0.234，P 值 < 0.001；肝移植：HR：0.102，95％CI：0.072-0.145，P值<0.001），化疗（HR：0.561，95％CI：0.471-0.668，P值<0.001）和放疗（HR： 0.641，95% CI：0.463-0.887，P 值：0.007）是 ANHC 患者的独立预后因素。我们开发了用于预测 ANHC 患者 OS 和 CSS 的列线图模型，具有良好的预测性能。