He Xuanhong, Lu Minxun, Hu Xin, Li Longqing, Zou Chang, Luo Yi, Zhou Yong, Min Li, Tu Chongqi
Department of Orthopedics, Orthopaedic Research Institute, West China Hospital, Sichuan University, Chengdu, China.
Front Oncol. 2022 Jul 22;12:952228. doi: 10.3389/fonc.2022.952228. eCollection 2022.
The relationship between indeterminate pulmonary nodules (IPNs) and metastasis is difficult to determine. We expect to explore a predictive model that can assist in indicating the nature of IPNs, as well as predicting the probability of metachronous metastasis in osteosarcoma patients.
We conducted a retrospective study including 184 osteosarcoma patients at West China Hospital from January 2016 to January 2021. Hematological markers and clinical features of osteosarcoma patients were collected and analyzed.
In this study, we constructed an osteosarcoma immune prognostic index (OIPI) based on the lung immune prognostic index (LIPI). Compared to other hematological markers and clinical features, OIPI had a better ability to predict metastasis. OIPI divided 184 patients into four groups, with the no-OIPI group (34 patients), the light-OIPI group (35 patients), the moderate-OIPI group (75 patients), and the severe-OIPI group (40 patients) (P < 0.0001). Subgroup analysis showed that the OIPI could have a stable predictive effect in both the no-nodule group and the IPN group. Spearman's rank correlation test and Kruskal-Wallis test demonstrated that the OIPI was related to metastatic site and metastatic time, respectively. In addition, patients with IPNs in high-OIPI (moderate and severe) groups were more likely to develop metastasis than those in low-OIPI (none and light) groups. Furthermore, the combination of OIPI with IPNs can more accurately identify patients with metastasis, in which the high-OIPI group had a higher metastasis rate, and the severe-OIPI group tended to develop metastasis earlier than the no-OIPI group. Finally, we constructed an OIPI-based nomogram to predict 3- and 5-year metastasis rates. This nomogram could bring net benefits for more patients according to the decision curve analysis and clinical impact curve.
This study is the first to assist chest CT in diagnosing the nature of IPNs in osteosarcoma based on hematological markers. Our findings suggested that the OIPI was superior to other hematological markers and that OIPI can act as an auxiliary tool to determine the malignant transformation tendency of IPNs. The combination of OIPI with IPNs can further improve the metastatic predictive ability in osteosarcoma patients.
难以确定肺内不确定结节（IPN）与转移之间的关系。我们期望探索一种预测模型，以协助判断IPN的性质，并预测骨肉瘤患者异时性转移的概率。
我们进行了一项回顾性研究，纳入了2016年1月至2021年1月在华西医院就诊的184例骨肉瘤患者。收集并分析了骨肉瘤患者的血液学标志物和临床特征。
在本研究中，我们基于肺免疫预后指数（LIPI）构建了骨肉瘤免疫预后指数（OIPI）。与其他血液学标志物和临床特征相比，OIPI具有更好的转移预测能力。OIPI将184例患者分为四组，即无OIPI组（34例患者）、轻度OIPI组（35例患者）、中度OIPI组（75例患者）和重度OIPI组（40例患者）（P < 0.0001）。亚组分析表明，OIPI在无结节组和IPN组中均具有稳定的预测效果。Spearman等级相关检验和Kruskal-Wallis检验分别表明，OIPI与转移部位和转移时间相关。此外，高OIPI（中度和重度）组中患有IPN的患者比低OIPI（无和轻度）组的患者更易发生转移。此外，OIPI与IPN相结合能够更准确地识别发生转移的患者，其中高OIPI组的转移率更高，且重度OIPI组比无OIPI组更倾向于更早发生转移。最后，我们构建了基于OIPI的列线图以预测3年和5年转移率。根据决策曲线分析和临床影响曲线，该列线图可为更多患者带来净效益。
本研究首次基于血液学标志物辅助胸部CT诊断骨肉瘤中IPN的性质。我们的研究结果表明，OIPI优于其他血液学标志物，并且OIPI可作为确定IPN恶变倾向的辅助工具。OIPI与IPN相结合可进一步提高骨肉瘤患者转移预测能力。
