Journal of Jilin University(Medicine Edition) ›› 2024, Vol. 50 ›› Issue (1): 188-197.doi: 10.13481/j.1671-587X.20240123
• Research in clinical medicine • Previous Articles Next Articles
Xiaopeng YU1,Renyi YANG1,Zuomei HE2(
),Puhua ZENG2,3(
)
Received:2023-02-16
Online:2024-01-28
Published:2024-01-31
Contact:
Zuomei HE,Puhua ZENG
E-mail:281144800@qq.com;zph120@126.com
CLC Number:
Xiaopeng YU,Renyi YANG,Zuomei HE,Puhua ZENG. Establishment and validation of nomogram of cancer specific survival of patients with hepatocellular carcinoma with negative alpha fetoprotein based on SEER Database[J].Journal of Jilin University(Medicine Edition), 2024, 50(1): 188-197.
Tab.1
Basic data of AFP negative HCC patients in training cohort and iternal validation cohort"
| Characteristic | Training (n=1 822) | Internal validation (n=782) | χ2 | P | Characteristic | Training (n=1 822) | Internal validation (n=782) | χ2 | P |
|---|---|---|---|---|---|---|---|---|---|
| Age(year) | 0.58 | 0.450 | Lung metastasis | 0.20 | 0.650 | ||||
| <75 | 1 413 (77.55) | 617 (78.90) | Yes | 30 (1.65) | 11 (1.41) | ||||
| ≥75 | 409 (22.45) | 165 (21.10) | No | 1 792 (98.35) | 771(98.59) | ||||
| Gender | 2.56 | 0.110 | Tumor size | 3.45 | 0.180 | ||||
| Female | 420 (23.05) | 158 (20.20) | <38 mm | 770 (42.26) | 361(46.16) | ||||
| Male | 1 402 (76.95) | 624 (79.80) | 38-82 mm | 714 (39.19) | 283(36.19) | ||||
| Grade | 2.30 | 0.470 | >82 mm | 338 (18.55) | 138(17.65) | ||||
| GradeⅠ | 771 (42.32) | 312 (39.90) | Marital status | 1.32 | 0.720 | ||||
| GradeⅡ | 865 (47.48) | 383 (48.98) | Divorce | 206 (11.31) | 77 (9.85) | ||||
| GradeⅢ | 174 (9.55) | 84 (10.74) | Married | 1 119 (61.42) | 490(62.66) | ||||
| GradeⅣ | 12 (0.66) | 3 (0.38) | Single | 339 (18.61) | 144(18.41) | ||||
| Surgery | 0.02 | 0.900 | Widowed | 158 (8.67) | 71 (9.08) | ||||
| Yes | 1 076 (59.06) | 464 (59.34) | T stage | 2.39 | 0.500 | ||||
| No | 746 (40.94) | 318 (40.66) | T1 | 1 098 (60.26) | 475(60.74) | ||||
| Radiotherapy | 2.07 | 0.150 | T2 | 408 (22.39) | 183(23.40) | ||||
| Yes | 164 (9.00) | 57 (7.29) | T3 | 269 (14.76) | 111(14.19) | ||||
| No | 1 658 (91.00) | 725 (92.71) | T4 | 47 (2.58) | 13 (1.66) | ||||
| Chemotherapy | 0.11 | 0.740 | N stage | 1.35 | 0.250 | ||||
| Yes | 612 (33.59) | 268 (34.27) | N0 | 1 764 (96.82) | 750 (95.91) | ||||
| No | 1 210 (66.41) | 514 (65.73) | N1 | 58 (3.18) | 32 (4.09) | ||||
| Bone metastasis | 0.09 | 0.770 | M stage | 0.81 | 0.370 | ||||
| Yes | 26 (1.43) | 10 (1.28) | M0 | 1 737 (95.33) | 739 (94.50) | ||||
| No | 1 796 (98.57) | 772 (98.72) | M1 | 85 (4.67) | 43 (5.50) |
Tab.2
Basic data of AFP negative HCC patients in training cohort and external validation cohort"
| Characteristic | Training (n=1 822) | External validation (n=101) | χ2 | P |
|---|---|---|---|---|
| Age(year) | 11.05 | < 0.05 | ||
| <75 | 1 413 (77.55) | 93 (92.08) | ||
| ≥75 | 409 (22.45) | 8 (7.92) | ||
| Grade | 36.55 | < 0.05 | ||
| GradeⅠ | 771 (42.32) | 42 (41.58) | ||
| GradeⅡ | 865 (47.48) | 31 (30.69) | ||
| GradeⅢ | 174 (9.55) | 28 (27.72) | ||
| GradeⅣ | 12 (0.66) | 0 (0) | ||
| Surgery | 55.63 | < 0.05 | ||
| Yes | 1 076 (59.06) | 21 (20.79) | ||
| No | 746 (40.94) | 80 (79.21) | ||
| Radiotherapy | 11.68 | < 0.05 | ||
| Yes | 164 (9.00) | 20 (19.80) | ||
| No | 1 658 (91.00) | 81 (80.20) | ||
| Chemotherapy | 17.48 | < 0.05 | ||
| Yes | 612 (33.59) | 55 (54.46) | ||
| No | 1 210 (66.41) | 46 (45.54) | ||
| Lung metastasis | 67.35 | < 0.05 | ||
| Yes | 30 (1.65) | 15 (14.85) | ||
| No | 1 792 (98.35) | 86 (85.15) | ||
| Tumor size | 95.86 | < 0.05 | ||
| <38 mm | 770 (42.26) | 14 (13.86) | ||
| 38-82 mm | 714 (39.19) | 28 (27.72) | ||
| >82 mm | 338 (18.55) | 59 (58.42) | ||
| Marital status | 61.43 | < 0.05 | ||
| Divorced | 206 (11.31) | 0 (0) | ||
| Married | 1 119 (61.42) | 101 (100.00) | ||
| Single | 339 (18.61) | 0 (0) | ||
| Widowed | 158 (8.67) | 0 (0) | ||
| T stage | 217.05 | < 0.05 | ||
| T1 | 1 098 (60.26) | 14 (13.86) | ||
| T2 | 408 (22.39) | 23 (22.77) | ||
| T3 | 269 (14.76) | 36 (35.64) | ||
| T4 | 47 (2.58) | 28 (27.72) | ||
| M stage | 117.57 | < 0.05 | ||
| M0 | 1 737 (95.33) | 69 (68.32) | ||
| M1 | 85 (4.67) | 32 (31.68) |
| 1 | BRAY F, FERLAY J, SOERJOMATARAM I, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J].CA Cancer J Clin,2018,68(6):394-424. |
| 2 | YAN B, SU B B, BAI D S, et al. A practical nomogram and risk stratification system predicting the cancer-specific survival for patients with early hepatocellular carcinoma[J]. Cancer Med, 2021,10(2): 496-506. |
| 3 | GALLE P R, FOERSTER F, KUDO M, et al. Biology and significance of alpha-fetoprotein in hepatocellular carcinoma[J]. Liver Int, 2019, 39(12): 2214-2229. |
| 4 | YANG D S, ZHU M Q, XIONG X Y, et al. Clinical features and prognostic factors in patients with microvascular infiltration of hepatocellular carcinoma: development and validation of a nomogram and risk stratification based on the SEER database[J]. Front Oncol, 2022, 12: 987603. |
| 5 | 中华人民共和国国家卫生健康委员会.原发性肝癌诊疗指南(2022年版)[J]. 肿瘤综合治疗电子杂志, 2022,8(2): 16-53. |
| 6 | CUCCHETTI A, PISCAGLIA F, GRIGIONI A D, et al. Preoperative prediction of hepatocellular carcinoma tumour grade and micro-vascular invasion by means of artificial neural network: a pilot study[J]. J Hepatol, 2010, 52(6): 880-888. |
| 7 | WANG M J, DEVARAJAN K, SINGAL A G, et al. The doylestown algorithm: a test to improve the performance of AFP in the detection of hepatocellular carcinoma[J]. Cancer Prev Res, 2016, 9(2): 172-179. |
| 8 | GIANNINI E G, MARENCO S, BORGONOVO G, et al. Alpha-fetoprotein has no prognostic role in small hepatocellular carcinoma identified during surveillance in compensated cirrhosis[J]. Hepatology, 2012, 56(4): 1371-1379. |
| 9 | BAI D S, ZHANG C, CHEN P, et al. The prognostic correlation of AFP level at diagnosis with pathological grade, progression, and survival of patients with hepatocellular carcinoma[J]. Sci Rep,2017,7(1):12870. |
| 10 | FARINATI F, MARINO D, DE GIORGIO M, et al. Diagnostic and prognostic role of alpha-fetoprotein in hepatocellular carcinoma: both or neither?[J]. Am J Gastroenterol, 2006, 101(3): 524-532. |
| 11 | JIANG S J, ZHAO R J, LI Y R, et al. Prognosis and nomogram for predicting postoperative survival of duodenal adenocarcinoma: a retrospective study in China and the SEER database[J]. Sci Rep, 2018, 8(1): 7940. |
| 12 | WU J, ZHANG H B, LI L, et al. A nomogram for predicting overall survival in patients with low-grade endometrial stromal sarcoma: a population-based analysis[J]. Cancer Commun, 2020, 40(7): 301-312. |
| 13 | VICKERS A J, ELKIN E B. Decision curve analysis: a novel method for evaluating prediction models[J]. Med Decis Making, 2006, 26(6): 565-574. |
| 14 | CAMP R L, DOLLED-FILHART M, RIMM D L. X-tile:a new bio-informatics tool for biomarker assessment and outcome-based cut-point optimization[J]. Clin Cancer Res, 2004, 10(21): 7252-7259. |
| 15 | TAN X J, WANG J K, TANG J, et al. A nomogram for predicting cancer-specific survival in children with wilms tumor: a study based on SEER database and external validation in China[J]. Front Public Health, 2022, 10: 829840. |
| 16 | HUANG X, LUO Z, LIANG W, et al. Survival nomogram for young breast cancer patients based on the SEER database and an external validation cohort[J]. Ann Surg Oncol, 2022, 29(9): 5772-5781. |
| 17 | LIU K, HUANG G B, CHANG P K, et al. Construction and validation of a nomogram for predicting cancer-specific survival in hepatocellular carcinoma patients[J]. Sci Rep, 2020, 10(1): 21376. |
| 18 | TERENTIEV A A, MOLDOGAZIEVA N T. Alpha-fetoprotein: a renaissance[J].Tumour Biol,2013,34(4): 2075-2091. |
| 19 | TOYODA H, KUMADA T, TADA T, et al. Clinical utility of highly sensitive Lens culinaris agglutinin-reactive alpha-fetoprotein in hepatocellular carcinoma patients with alpha-fetoprotein <20 ng/mL[J]. Cancer Sci, 2011, 102(5): 1025-1031. |
| 20 | XU Y Y, LU X, MAO Y L, et al. Clinical diagnosis and treatment of alpha-fetoprotein-negative small hepatic lesions[J]. Chung Kuo Yen Cheng Yen Chiu, 2013, 25(4): 382-388. |
| 21 | ZHANG X F, QI X, MENG B, et al. Prognosis evaluation in alpha-fetoprotein negative hepatocellular carcinoma after hepatectomy: comparison of five staging systems[J]. Eur J Surg Oncol, 2010, 36(8): 718-724. |
| 22 | GÓMEZ-RODRÍGUEZ R, ROMERO-GUTIÉRREZ M, ARTAZA-VARASA T, et al. The value of the Barcelona Clinic Liver Cancer and alpha-fetoprotein in the prognosis of hepatocellular carcinoma[J]. Rev Esp Enferm Dig, 2012, 104(6): 298-304. |
| 23 | GAN W, HUANG J L, ZHANG M X, et al. New nomogram predicts the recurrence of hepatocellular carcinoma in patients with negative preoperative serum AFP subjected to curative resection[J]. J Surg Oncol, 2018, 117(7): 1540-1547. |
| 24 | REN N, QIN L X, TU H, et al. The prognostic value of circulating plasma DNA level and its allelic imbalance on chromosome 8p in patients with hepatocellular carcinoma[J]. J Cancer Res Clin Oncol, 2006, 132(6): 399-407. |
| 25 | WANG X P, MAO M J, HE Z L, et al. Development and validation of a prognostic nomogram in AFP-negative hepatocellular carcinoma[J]. Int J Biol Sci, 2019, 15(1): 221-228. |
| 26 | ZHAN H, ZHAO X, LU Z X, et al. Correlation and survival analysis of distant metastasis site and prognosis in patients with hepatocellular carcinoma[J]. Front Oncol, 2021, 11: 652768. |
| 27 | ZHANG W, JI L C, WANG X J, et al. Nomogram predicts risk and prognostic factors for bone metastasis of pancreatic cancer: a population-based analysis[J]. Front Endocrinol, 2021, 12: 752176. |
| 28 | WANG H M, SHAN X F, ZHANG M, et al. Homogeneous and heterogeneous risk and prognostic factors for lung metastasis in colorectal cancer patients[J]. BMC Gastroenterol, 2022, 22(1): 193. |
| 29 | TONG Y X, HUANG Z H, HU C, et al. Independent risk factors evaluation for overall survival and cancer-specific survival in thyroid cancer patients with bone metastasis: a study for construction and validation of the predictive nomogram[J].Medicine,2020,99(36):e21802. |
| 30 | HUANG Z H, HU C, LIU K W, et al. Risk factors, prognostic factors, and nomograms for bone metastasis in patients with newly diagnosed infiltrating duct carcinoma of the breast: a population-based study[J]. BMC Cancer, 2020, 20(1): 1145. |
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