Skip to main content

Prognostic significance of the CRAFITY score in hepatocellular carcinoma treated with immunotherapy: a systematic review and meta-analysis

Abstract

Background

This meta-analysis aimed to assess the performance of the CRAFITY (CRP and AFP in immunotherapy) score as a prognostic factor in hepatocellular carcinoma (HCC) treated with immunotherapy.

Methods

The PubMed, Cochrane Library, and Web of Science databases were searched for published studies. Hazard ratios (HRs) with 95% confidence intervals (CIs) for overall survival (OS) and progression-free survival (PFS) outcomes were pooled using fixed- and random-effects models. Odds ratios (ORs) with 95% CI were used to measure the association of individual CRAFITY scores with the disease control rate (DCR).

Results

Four eligible studies comprising 786 patients were included. The results indicate that a lower CRAFITY score is a significant predictor of better OS (HR = 0.22, 95% CI: 0.10–0.50) and PFS (HR = 0.36, 95% CI: 0.23–0.55) outcomes. In addition, the DCR was significantly higher in patients with lower CRAFITY scores (OR = 3.16, 95% CI: 2.00–4.99). A significant positive association between low CRAFITY scores and favorable prognoses was also observed in Barcelona Clinic Liver Cancer stage B/C/D patients.

Conclusion

In this study, a low CRAFITY score was associated with better overall outcomes in HCC patients treated with immunotherapy. However, this finding requires further investigation.

Peer Review reports

Introduction

Liver cancer remains a growing global health threat [1], and it is estimated that over 1 million patients will be affected annually by 2050 [2]. The 5-year survival rate for all stages combined is 18%. The poor outcome of hepatocellular carcinoma (HCC) patients results from late diagnosis and the refractory nature of the disease. Currently, liver cancer therapies consist of aggressive multimodal treatments, including surgery, transarterial chemoembolization, transarterial radioembolization, radiofrequency ablation, molecular targeted therapy, and immunotherapy [3,4,5]. Despite the advancement in comprehensive therapy and expected improvement in clinical outcomes, relapse, progression, and treatment failure remain frequent.

Immune checkpoint inhibitors (ICIs) are one of the most important classes of immunotherapy drugs that target negative regulatory proteins on T cells and enhance T-cell activation [6]. Previous studies have identified several predictive markers for immunotherapy responses derived from patient genomics data, such as noncoding and coding RNAs, DNA methylation, and mutational burden [7, 8]. However, there are currently no robust markers that predict clinical response.

Alpha-fetoprotein (AFP) is expressed in 70–80% of HCC patients, serving as a biomarker for diagnosis and surveillance [9]. C-reactive protein (CRP) is an acute-phase reactant protein synthesized by hepatocytes in response to inflammatory cytokines and is thought to be an important prognostic marker of liver cancer [10]. The combined use of serum AFP and CRP values (i.e., the CRAFITY score) has recently been recommended for identifying patients who will benefit from immunotherapy on the basis of the results of a retrospective multicenter study [11]. However, this study was retrospective, and synthetic evidence is lacking. Here, a systematic review and meta-analysis was performed to evaluate the significance of the combined use of AFP and CRP values in predicting the clinical outcomes of liver cancer patients treated with immunotherapy.

Materials and methods

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses statements were followed [12].

Data sources and search

Two investigators conducted an independent literature search using the PubMed, Embase, Cochrane Library, and Web of Science databases from the databases’ inception to May 31, 2022 (Ming and Yilin). The following key terms were used: “Alpha-fetoprotein,” “C-reactive protein,” and “CRAFITY score.” The cited references of the relevant systematic reviews and conference proceedings were manually cross-checked to identify additional literature. Articles pertinent to liver cancer immunotherapy were selected for this meta-analysis. Searches were not restricted by language, country, or publication date. Articles were initially screened based on title and abstract reading, and then full texts of potentially relevant publications were obtained and reviewed by two authors independently (Ming and Yilin) to determine the publications’ eligibility. Any discrepancies were resolved by discussion, and a third assessor arbitrated any disagreements.

Selection criteria

Eligible studies that conformed to the following criteria were included in this meta-analysis. (i) Hepatocellular carcinoma patients received ICIs. (ii) The pretreatment CRAFITY score comprising two indicators, AFP and CRP (0 points (AFP < 100 ng/mL and CRP < 1 mg/dL) indicating a low CRAFITY score, 1 point (either AFP ≥ 100 ng/mL or CRP ≥ 1 mg/dL) indicating intermediate, and 2 points (AFP ≥ 100 ng/mL and CRP ≥ 1 mg/dL) indicating high) was used as a prognostic factor. (iii) The main outcomes of interest were overall survival (OS) and progression-free survival (PFS). (iv) Tumor control or progression was defined according to radiological evaluations.

Data extraction

Data were extracted from the retrieved full-text articles independently by two reviewers (Ming and Yilin). First, information from eligible publications was extracted, including the first author, study design, sample size, demographic features, clinicopathological characteristics, and immunotherapy regimens. Second, information about the following clinical data from included trials and their supplementary documentation was extracted, including the hazard ratio (HR) and 95% CI for OS and PFS and the number of patients with an antitumor response for calculating the disease control rate (DCR). Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 or modified RECIST (mRECIST) was used in the four included studies [11, 13,14,15]; the DCR was defined as the percentage of patients achieving complete or partial responses or with stable disease.

Quality assessment

The Newcastle–Ottawa Scale [16] was used to assess study quality. The scale consists of three parameters: selection, comparability, and outcome assessment. The maximum possible score is 9 points, and studies with a score > 6 are regarded as high-quality.

Statistical analysis

RevMan (version 5.3, Cochrane Collaboration) was applied to pool and analyze data. Pooled HR and 95% CI estimates for OS and PFS outcomes were obtained from each article, where possible. The odds ratios (OR) and 95% CI for the DCR were also retrieved from each article. If HRs with 95% CI were not reported, HRs with 95% CI were derived indirectly from the Kaplan–Meier curves using the methods described by Tierney [17]. Heterogeneity among studies was assessed using Cochran’s Q statistic and I2 statistics. Heterogeneity was considered statistically significant when I2 > 50% or P < 0.10. I2 values of 0–50%, 50–75%, and 75–100% represent low, moderate, and high heterogeneities, respectively. A fixed-effects model was used when heterogeneity existed; otherwise, a random-effects model was used.

Results

Identification of studies and study characteristics

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow diagram is presented in Fig. 1. The systematic search yielded 1,094 records through electronic searches of the PubMed (138 records), Embase (638 records), Web of Science (312 records), and Cochrane Library (6 records) databases. After duplicates were removed, 182 records remained. Based on the title and abstract, 177 irrelevant records were excluded. Four full-text articles were retrieved by two independent reviewers for further detailed assessment. One article was excluded [18] due to the lack of survival information. Eventually, four studies [11, 13,14,15] were included, comprising 786 hepatocellular carcinoma patients treated with immunotherapy. The overall quality of the four cohort studies [11, 13,14,15] was moderate; the Newcastle–Ottawa Scale scores ranged from 7 to 8.

Fig. 1
figure 1

PRISMA diagram showing the identification of the eligible studies and reasons for exclusion

Four studies [11, 13,14,15] investigated HCC patients undergoing immunotherapy; immunotherapeutic regimens included anti-programmed death (ligand) 1 (anti-PD-(L)1)-based immunotherapy monotherapy plus bevacizumab/ramucirumab/TKI and anti-CTL-4/anti-CD38. Three studies [13,14,15] investigated patients with Barcelona Clinic Liver Cancer (BCLC) stage B or later, with only one study [11] including patients with BCLC stage A. In particular, Scheiner et al. reported treatment data for two independent cohorts of HCC patients. A summary of the baseline patient information is presented in Table 1.

Table 1 Patient demographics and baseline characteristics

Predicted effect of CRAFITY score on OS Outcomes among HCC patients treated with immunotherapy

Each of these four studies [11, 13,14,15] reported survival data and assessed the predicted effects of the CRAFITY score on OS outcomes among HCC patients. OS was defined as the time from the start of immunotherapy until the date of death or last follow-up in the four publications [11, 13,14,15].

A random-effects model was used to pool the included studies [11, 13,14,15] and demonstrated that patients with a low CRAFITY score (0 points) had better OS outcomes than those with a high CRAFITY score (2 points) (HR = 0.24, 95% CI: 0.13–0.45, P < 0.00001), with a moderate heterogeneity between studies (I2 = 34%, P = 0.21) (Fig. 2A).

Fig. 2
figure 2

Forest plot depicting improved overall survival outcomes with low and intermediate CRAFITY scores in the subgroup analysis according to BCLC stage. (A) The OS outcomes of BCLC A/B/C/D patients with CRAFITY score: 0. (B) The OS outcomes of BCLC A/B/C/D patients with CRAFITY score: 1. (C) The OS outcomes of BCLC B/C/D patients with CRAFITY score: 0

Analyses of patients pooled for intermediate (1 point) and high (2 points) CRAFITY scores showed similar results. An intermediate CRAFITY score was also significantly associated with a better prognosis (HR = 0.50, 95% CI: 0.36–0.69, P < 0.0001). The meta-analysis approach showed low heterogeneity (I2 = 22%, P = 0.28). (Fig. 2B). Considerable heterogeneity is observed in the aforementioned results. A stratified analysis according to the BCLC staging demonstrated a significant association between low CRAFITY scores and better OS outcomes among BCLC stage B/C/D patients treated with immunotherapy (HR = 0.27, 95% CI: 0.14–0.52, P < 0.0001), with no heterogeneity (I2 = 0%, P = 0.41) (Fig. 2C).

Predicted effect of the CRAFITY score on PFS outcomes among HCC patients treated with immunotherapy

Hatanaka et al. [13] and Teng et al. [14] reported the PFS outcomes of patients with liver cancer after immunotherapy. In these two publications [13, 14], PFS was defined as the time from the initial immunotherapy until radiological disease progression or death.

The pooled data indicated that a low CRAFITY score was associated with increased PFS rates in HCC patients treated with immunotherapy with a pooled HR estimate of 0.36 (95% CI: 0.23–0.55; Fig. 3A), without any heterogeneity (I2 = 0%, P = 0.39). Next, a subgroup analysis was performed according to the BCLC staging system. As shown in Fig. 3B, BCLC stage B/C/D patients with low CRAFITY scores had better PFS outcomes after receiving immunotherapy (HR = 0.42, 95% CI: 0.26–0.68, P = 0.0004), with no heterogeneity (I2 = 0%, P = 0.72).

Fig. 3
figure 3

Forest plot depicting improved progression-free survival outcomes among patients with low CRAFITY scores in the subgroup analysis according to BCLC stage. (A) The PFS outcomes of BCLC stage A/B/C/D patients. (B) The PFS outcomes of BCLC stage B/C/D patients

The CRAFITY score predicts radiological response in HCC patients treated with immunotherapy

Liver cancer patient responses to immunotherapy were determined by radiologic monitoring (RECIST/mRECIST) in all four publications [11, 13,14,15]. The difference in responses to immunotherapy among the patients with 0 (CRAFITY-low), 1 (CRAFITY-intermediate), and 2 points (CRAFITY-high) was investigated.

The pooled result showed a significantly increased DCR in the CRAFITY-low and CRAFITY-intermediate groups (OR = 3.03, 95% CI: 1.98–4.64, P < 0.00001), with no heterogeneity (I2 = 0%, P = 0.69) (Fig. 4A) compared with that in the CRAFITY-high group. In addition, the CRAFITY-low group also showed a higher DCR than the CRAFITY-high group (OR = 4.55, 95% CI: 2.66–7.79, P < 0.00001), with no heterogeneity (I2 = 0%, P = 0.51) (Fig. 4B).

Fig. 4
figure 4

Forest plot depicting the disease control rate in the subgroup analysis according to CRAFITY score. (A)The DCR of patients with CRAFITY score: 0,1. (B) The DCR of patients with CRAFITY score: 0

Discussion

The current estimates indicate that liver cancer is the seventh most common cancer and the fourth main cause of cancer-related death worldwide [19]. Over half of liver cancer patients are diagnosed with advanced-stage disease. Nevertheless, systemic therapy has been shown to improve local and systemic liver cancer control [5, 20]. The clinical use of ICIs is rapidly expanding; atezolizumab plus bevacizumab was recently approved as first-line therapy for unresectable, advanced HCC [21]. Although immunotherapy has improved the prognosis of patients with advanced liver cancer, it is important to note that only a subset of patients benefits from this intervention [22]. To the best of our knowledge, there is no uniform biomarker to predict liver tumor responses to ICIs. In this study, we specifically sought to identify a validated clinical predictor of positive outcomes for ICI.

Recently, Scheiner et al. proposed using the CRAFITY score to predict the treatment response and survival of patients with liver cancer receiving immunotherapy with PD-(L)1 antibodies [11]. However, more evidence is needed to confirm the predictive ability of the CRAFITY score in immunotherapy. In this meta-analysis, we first assessed the relationship between the CRAFITY score and patient prognosis. Overall, we included four trials enrolling 786 HCC patients treated with immunotherapy. The results of the current study demonstrated that patients with a low CRAFITY score had better OS and DFS outcomes high DCRs. In BCLC stage A/B/C/D patients, the pooled HRs of OS outcomes were moderately heterogeneous. Taking this further, the OS of patients with CRAFITY score 1 was also longer than those with CRAFITY score 2. A stratified analysis by the BCLC staging (BCLC B/C/D) showed remarkably decreased heterogeneity, but the prognostic significance was not reduced. ICI failure as monotherapy in a phase III trial for advanced HCC was recently reported [23]. However, another phase III randomized trial found that the endpoint OS outcomes were significantly improved by atezolizumab plus bevacizumab compared with sorafenib [24]. Furthermore, systemic administration of checkpoint blockade can result in immune-related adverse events (irAEs) [25]. Despite combining immunotherapy and targeted therapy, approximately half of liver cancer patients do not respond to ICIs. A reliable clinical marker will enable the selection of patients maximally responsive to immunotherapy and reduce the application of therapy to patients who are unlikely to benefit.

AFP is an important serological indicator of HCC that was previously identified in human fetal serum [26]. To date, the AFP level is recommended for routine screening, diagnosis, and prognostic stratification of liver cancer [9, 27, 28]. AFP levels are also used to identify patients with liver tumors who are suitable for liver transplantation [29]. CRP is now considered to have prognostic value in patients with cancer independent of tumor stage. A recent review discussed the in-depth link between traditional circulating inflammatory markers, such as CRP, IL-6, and systemic inflammation in cancer patients [30]. As one of the hallmarks of cancer, cancer-associated inflammation is an important event in tumor progression and may affect the tumor microenvironment. Chronic inflammation is a key inducer of the immunosuppressive microenvironment. A previous study revealed the lymphocyte-to-monocyte ratio to be a positive prognostic factor in colorectal cancer patients with liver metastasis after radiofrequency ablation [31]. Zhang et al. found that patients with high CRP levels have shorter PFS times than those with low CRP after PD-1 inhibitor treatment [32]. Therefore, our meta-analysis specifically focused on whether combining AFP and CRP values can serve as a biomarker for immunotherapy. In the current analysis, all included trials assessed survival via the CRAFITY score, and tumor immunotherapy produced better therapeutic effects in patients with a low CRAFITY score.

The response evaluation was performed radiologically according to RECIST version 1.1 or mRECIST in the four included studies; a high DCR was significantly associated with low and intermediate CRAFITY scores. Furthermore, the CRAFITY score system is not a risk prediction model, as it does not require expert computational skills to calculate patient data. Thus, the CRAFITY score might be a practical, effective tool for stratifying liver cancer patients and enhance the response rate of ICI.

This study has several limitations. First, only four good-quality retrospective studies from six countries (Austria, Germany, Italy, Switzerland, China and Japan) were included after an exhaustive systematic search. Prospective randomized studies and a large sample size are needed before this CRAFITY score can be routinely recommended. Second, two studies used atezolizumab plus bevacizumab, one used anti-PD-(L)1 plus lenvatinib and one used anti-PD-(L)1 monotherapy or a combination with targeted treatment. Third, the different BCLC stages of the patients is a limitation and differences between stage B, C, and D patients may be obscured. To fully understand the effects of tumor burden, sufficient data for prespecified subgroup analyses are required.

Conclusion

In this meta-analysis, the CRAFITY score was sufficient to distinguish outcome differences among patients treated with immunotherapy. Low and intermediate CRAFITY scores were associated with a lower risk of death and increased response rates to immunotherapy among HCC patients. Therefore, these findings provide some evidence for the clinical applicability of the CRAFITY score.

Data availability

All data generated or analyzed during this study are included in this published article.

Abbreviations

CRAFITY score:

CRP and AFP in immunotherapy score

HRs:

Hazard ratios

CI:

Confidence interval

PFS:

Progression-free survival

OS:

Overall survival

ORs:

Odds ratios

BCLC:

Barcelona Clinic Liver Cancer

HCC:

Hepatocellular carcinoma

PRISMA:

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

WOS:

Web of Science

CRP:

C-reactive protein

AFP:

Alpha-fetoprotein

DCR:

Disease control rate

RECIST:

Response Evaluation Criteria in Solid Tumors

References

  1. Llovet JM, Kelley RK, Villanueva A, Singal AG, Pikarsky E, Roayaie S, Lencioni R, Koike K, Zucman-Rossi J, Finn RS. Hepatocellular carcinoma. Nat Reviews Disease Primers. 2021;7(1):7.

    Article  Google Scholar 

  2. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. Cancer J Clin. 2018;68(6):394–424.

    Article  Google Scholar 

  3. Wong KM, King GG, Harris WP. The Treatment Landscape of Advanced Hepatocellular Carcinoma. Curr Oncol Rep. 2022;24(7):917–27.

    Article  CAS  PubMed  Google Scholar 

  4. Rognoni C, Ciani O, Sommariva S, Facciorusso A, Tarricone R, Bhoori S, Mazzaferro V. Trans-arterial radioembolization in intermediate-advanced hepatocellular carcinoma: systematic review and meta-analyses. Oncotarget. 2016;7(44):72343–55.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Yang JD, Hainaut P, Gores GJ, Amadou A, Plymoth A, Roberts LR. A global view of hepatocellular carcinoma: trends, risk, prevention and management. Nat reviews Gastroenterol Hepatol. 2019;16(10):589–604.

    Article  Google Scholar 

  6. Kidwell KM, Postow MA, Panageas KS. Sequential, multiple assignment, randomized trial designs in Immuno-oncology Research. Clin Cancer Res. 2018;24(4):730–6.

    Article  PubMed  Google Scholar 

  7. Jung H, Kim HS, Kim JY, Sun J-M, Ahn JS, Ahn M-J, Park K, Esteller M, Lee S-H, Choi JK. DNA methylation loss promotes immune evasion of tumours with high mutation and copy number load. Nat Commun. 2019;10(1):4278.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Kim K, Kim HS, Kim JY, Jung H, Sun J-M, Ahn JS, Ahn M-J, Park K, Lee S-H, Choi JK. Predicting clinical benefit of immunotherapy by antigenic or functional mutations affecting tumour immunogenicity. Nat Commun. 2020;11(1):951.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Kelley RK, Meyer T, Rimassa L, Merle P, Park JW, Yau T, Chan SL, Blanc JF, Tam VC, Tran A, et al. Serum alpha-fetoprotein levels and clinical outcomes in the Phase III CELESTIAL Study of Cabozantinib versus Placebo in patients with Advanced Hepatocellular Carcinoma. Clin Cancer Res. 2020;26(18):4795–804.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Chen W, Wang J-B, Abnet CC, Dawsey SM, Fan J-H, Yin L-Y, Yin J, Taylor PR, Qiao Y-L, Freedman ND. Association between C-reactive protein, incident liver cancer, and chronic liver disease mortality in the Linxian Nutrition intervention trials: a nested case-control study. Cancer Epidemiol Biomarkers Prev. 2015;24(2):386–92.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Scheiner B, Pomej K, Kirstein MM, Hucke F, Finkelmeier F, Waidmann O, Himmelsbach V, Schulze K, Felden Jv, Fründt TW, et al. Prognosis of patients with hepatocellular carcinoma treated with immunotherapy - development and validation of the CRAFITY score. J Hepatol. 2022;76(2):353–63.

    Article  CAS  PubMed  Google Scholar 

  12. Liberati MD, Altman ATetzlaffJ. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6(7):e1000097.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Hatanaka T, Kakizaki S, Hiraoka A, Tada T, Hirooka M, Kariyama K, Tani J, Atsukawa M, Takaguchi K, Itobayashi E et al. Prognostic impact of C-reactive protein and alpha-fetoprotein in immunotherapy score in hepatocellular carcinoma patients treated with atezolizumab plus bevacizumab: a multicenter retrospective study. Hepatology international 2022.

  14. Teng W, Lin C-C, Su C-W, Lin P-T, Hsieh Y-C, Chen W-T, Ho M-M, Wang C-T, Chai P-M, Hsieh JC-H, et al. Combination of CRAFITY score with alpha-fetoprotein response predicts a favorable outcome of atezolizumab plus bevacizumab for unresectable hepatocellular carcinoma. Am J cancer Res. 2022;12(4):1899–911.

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Yang Y, Ouyang J, Zhou Y, Zhou J, Zhao H. The CRAFITY score: a promising prognostic predictor for patients with hepatocellular carcinoma treated with tyrosine kinase inhibitor and immunotherapy combinations. J Hepatol. 2022;77(2):574–6.

    Article  CAS  PubMed  Google Scholar 

  16. Stang A. Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol. 2010;25(9):603–5.

    Article  PubMed  Google Scholar 

  17. Tierney JF, Stewart LA, Ghersi D, Burdett S, Sydes MR. Practical methods for incorporating summary time-to-event data into meta-analysis. Trials. 2007;8:16.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Lui TKL, Cheung KS, Leung WK. Machine learning models in the prediction of 1-year mortality in patients with advanced hepatocellular cancer on immunotherapy: a proof-of-concept study. Hep Intl. 2022;16(4):879–91.

    Article  Google Scholar 

  19. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global Cancer Statistics 2020: GLOBOCAN estimates of incidence and Mortality Worldwide for 36 cancers in 185 countries. Cancer J Clin. 2021;71(3):209–49.

    Article  Google Scholar 

  20. Shek D, Read SA, Nagrial A, Carlino MS, Gao B, George J, Ahlenstiel G. Immune-Checkpoint inhibitors for Advanced Hepatocellular Carcinoma: a Synopsis of Response Rates. Oncologist. 2021;26(7):e1216–25.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Casak SJ, Donoghue M, Fashoyin-Aje L, Jiang X, Rodriguez L, Shen Y-L, Xu Y, Jiang X, Liu J, Zhao H, et al. FDA approval Summary: Atezolizumab Plus Bevacizumab for the treatment of patients with Advanced Unresectable or Metastatic Hepatocellular Carcinoma. Clin Cancer Res. 2021;27(7):1836–41.

    Article  CAS  PubMed  Google Scholar 

  22. Zhu AX, Finn RS, Edeline J, Cattan S, Ogasawara S, Palmer D, Verslype C, Zagonel V, Fartoux L, Vogel A, et al. Pembrolizumab in patients with advanced hepatocellular carcinoma previously treated with sorafenib (KEYNOTE-224): a non-randomised, open-label phase 2 trial. Lancet Oncol. 2018;19(7):940–52.

    Article  PubMed  Google Scholar 

  23. Finn RS, Ryoo B-Y, Merle P, Kudo M, Bouattour M, Lim HY, Breder V, Edeline J, Chao Y, Ogasawara S, et al. Pembrolizumab as Second-Line therapy in patients with Advanced Hepatocellular Carcinoma in KEYNOTE-240: a Randomized, Double-Blind, phase III trial. J Clin Oncol. 2020;38(3):193–202.

    Article  CAS  PubMed  Google Scholar 

  24. Finn RS, Qin S, Ikeda M, Galle PR, Ducreux M, Kim T-Y, Kudo M, Breder V, Merle P, Kaseb AO, et al. Atezolizumab plus Bevacizumab in Unresectable Hepatocellular Carcinoma. N Engl J Med. 2020;382(20):1894–905.

    Article  CAS  PubMed  Google Scholar 

  25. Meserve J, Facciorusso A, Holmer AK, Annese V, Sandborn WJ, Singh S. Systematic review with meta-analysis: safety and tolerability of immune checkpoint inhibitors in patients with pre-existing inflammatory bowel diseases. Aliment Pharmacol Ther. 2021;53(3):374–82.

    CAS  PubMed  Google Scholar 

  26. Mizejewski GJ. Alpha-fetoprotein structure and function: relevance to isoforms, epitopes, and conformational variants. Exp Biol Med. 2001;226(5):377–408.

    Article  CAS  Google Scholar 

  27. McMahon BJ, Bulkow L, Harpster A, Snowball M, Lanier A, Sacco F, Dunaway E, Williams J. Screening for hepatocellular carcinoma in Alaska natives infected with chronic hepatitis B: a 16-year population-based study. Hepatology. 2000;32(4):842–6.

    Article  CAS  PubMed  Google Scholar 

  28. Chen VL, Xu D, Wicha MS, Lok AS, Parikh ND. Utility of Liquid Biopsy Analysis in detection of Hepatocellular Carcinoma, determination of prognosis, and Disease Monitoring: a systematic review. Clin Gastroenterol Hepatol. 2020;18(13):2879–902.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Gunsar F. Liver transplantation for hepatocellular carcinoma beyond the Milan criteria. Exp Clin Transplant. 2017;15:59–64.

    PubMed  Google Scholar 

  30. Sanghera C, Teh JJ, Pinato DJ. The systemic inflammatory response as a source of biomarkers and therapeutic targets in hepatocellular carcinoma. Liver Int. 2019;39(11):2008–23.

    Article  PubMed  Google Scholar 

  31. Facciorusso A, Prete VD, Crucinio N, Serviddio G, Vendemiale G, Muscatiello N. Lymphocyte-to-monocyte ratio predicts survival after radiofrequency ablation for colorectal liver metastases. World J Gastroenterol. 2016;22(16):4211–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Zhang Y, Lu L, He Z, Xu Z, Xiang Z, Nie R-C, Lin W, Chen W, Zhou J, Yin Y, et al. C-Reactive protein levels predict responses to PD-1 inhibitors in Hepatocellular Carcinoma Patients. Front Immunol. 2022;13:808101.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank LetPub (www.letpub.com) for its linguistic assistance during the preparation of this manuscript.

Funding

This research was supported by the National Natural Science Foundation of China (Nos. 81770566, 82000599), NHC Key Laboratory of Echinococcosis Prevention and Control (No. 2021WZK1004) and Health Commission of the Tibet Autonomous Region (No. 311220432).

Author information

Authors and Affiliations

Authors

Contributions

Ming and Wentao designed the study. Ming and Yilin performed the literature search, study selection and data extraction. Ming and Yilin performed the statistical analyses. Ming and Yilin wrote the first draft of the manuscript. All authors contributed to interpreting the data and critically reviewed the manuscript.

Corresponding author

Correspondence to Wentao Wang.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Yang, M., Pan, Y. & Wang, W. Prognostic significance of the CRAFITY score in hepatocellular carcinoma treated with immunotherapy: a systematic review and meta-analysis. BMC Cancer 23, 236 (2023). https://doi.org/10.1186/s12885-023-10686-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12885-023-10686-9

Keywords

  • CRAFITY score
  • Liver cancer
  • Prognosis
  • Immunotherapy
  • Meta-analysis