Tumour necrosis as a prognostic indicator in hepatocellular carcinoma

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Kauppila, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8134600/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 21 Apr, 2026 Read the published version in BMC Cancer → Version 1 posted 19 You are reading this latest preprint version Abstract Background Tumour necrosis is linked to worse outcomes in hepatocellular carcinoma (HCC). However, the relationship between the extent of necrosis in HCC and survival outcomes remains unclear, partly due to the lack of a standardised assessment method. This study analysed the prognostic significance of tumour necrosis and compared three quantification methods. Methods This retrospective study included 96 HCC patients from two Finnish centres, treated with surgical resection from 1986 to 2022. The extent of necrosis was assessed using three methods: (1) The average percentage method (proportion of necrosis relative to total tumour area), (2) the hotspot method (proportion of necrosis within a 2 mm hotspot), and (3) the linear method (diameter of the largest necrotic focus). Results Tumour necrosis was an independent risk factor for 5-year overall (HR 2.80, 95% CI 1.26–6.22, P = 0.011) and disease-specific mortality (HR 3.89, 95% CI 1.45–10.47, P = 0.007). Tumours with low (but nonzero) necrosis level, as measured by the average percentage, hotspot, and linear methods, were linked to poorer 5-year overall and disease-specific survival compared to tumours without necrosis. Conclusion Tumour necrosis is an independent risk factor for overall and disease-specific mortality in resected HCC. Lower (but nonzero) levels of necrosis were more strongly associated with a worse prognosis when compared with extensive necrosis, suggesting a complex relationship between tumour necrosis and disease progression. Hepatocellular carcinoma Surgical resection Prognostic biomarker Tumour necrosis Figures Figure 1 Figure 2 Figure 3 Background Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related mortality worldwide [ 1 ]. Chronic infection with hepatitis B and hepatitis C virus are the primary risk factors across most regions [ 2 ]. However, metabolic dysfunction-associated fatty liver disease (MAFLD) has become the leading cause of liver cirrhosis in Western countries [ 3 ] and will consequently emerge—with a delay—as the primary cause of HCC, causing a significant disease burden that will manifest over the coming decades. Although overall HCC management has improved, treatment strategies for surgically resectable HCC have remained largely unchanged for decades, and survival rates remain poor even after curative treatment [ 4 ]. There is currently no adjuvant treatment protocol for HCC, although the recurrence rate after curative surgery is as high as 70% [ 5 ]. Furthermore, there is no proven benefit from neoadjuvant therapies, even though nearly 70% of newly diagnosed cases present at an advanced stage [ 6 ]. This highlights the urgent need to identify biomarkers that can reliably predict tumour behaviour, recurrence risk and patient outcomes. Such biomarkers could facilitate more personalised and effective treatment strategies, guide therapeutic decision-making, and optimise treatment selection for each patient. A key characteristic of HCC pathogenesis is the role of persistent inflammation in the hepatic parenchyma [ 7 ]. Hepatocytes are damaged by various exogenous factors, leading to the release of molecular mediators like Damage-Associated Molecular Patterns (DAMPs) from dying liver cells [ 8 ]. This allows the host to respond to cell death through specific DAMP receptors, creating a local and systemic inflammatory response [ 7 , 8 , 9 ]. Persistent inflammation and cell death can result in progressive liver fibrosis and, culminating in cirrhosis, which is present in approximately 80–90% of HCC cases [ 7 ]. Furthermore, the aggressive tumour growth coupled with compromised oxygen delivery leads to tumour necrosis in a subset of HCC [ 10 ]. Tumour necrosis has been associated with poor prognosis in various solid cancers, including colorectal [ 11 ], renal [ 12 ], breast [ 13 ], lung [ 14 ] and pancreatic cancer [ 15 ], as well as HCC [ 9 , 16 – 19 ]. Tumour necrosis holds promise as a prognostic biomarker in HCC. Importantly, it can be analysed from haematoxylin- and eosin (H&E)-stained samples without complex or costly methods. However, the optimal approach for quantifying tumour necrosis in HCC remains inadequately defined [ 9 , 16 – 19 ]. While comparative studies have been conducted in some other malignancies, such as colorectal cancer [ 11 ], there is a lack of consensus on standardised assessment methods specific to HCC [ 9 ]. Our study aimed to determine the independent prognostic role of tumour necrosis in a bi-institutional cohort of HCC patients. Additionally, we sought to evaluate and compare methods for quantifying tumour necrosis in HCC. Methods Patient cohort A total of 99 HCC patients who were suitable for surgical resection were identified. Patients were diagnosed at Oulu University Hospital from 1986 to 2022 and at Central Finland Central Hospital from 1997 to 2022. Only histologically confirmed cases were included. Those who received neoadjuvant therapies (N = 3) were excluded, resulting in a final cohort of 96 patients. The study received approval from the Finnish Medicines Agency Fimea (Dnro FIMEA/2021/004928) and the Ethical Committee of the North Ostrobothnia Hospital District (EETTMK 81/2008). The study was conducted in accordance with the Declaration of Helsinki. Data collection We identified patients from the pathology archives using the ICD-10 code C22.0&. Relevant clinical information was collected from the patient charts and pathology reports. The 8th edition of the TNM classification was used for staging. Comorbidities were assessed using the Charlson Comorbidity Index (CCI), and postoperative complications were classified according to the Clavien-Dindo classification system. Cause of death and date of death were obtained from Statistics Finland. Follow-up data was gathered up to the end of 2022. Diagnostic H&E-stained tumour slides were retrieved from pathology archives and digitised using Aperio AT2 (Leica Biosystems, Wetzlar, Germany). The tumour grade was evaluated by a pathologist (J.P.V.) when it was not documented in the original pathology report. Tumour necrosis was analysed by one researcher (N.S.) using Aperio ImageScope. A second investigator (J.P.V.) assessed uncertain cases. Histopathological examination Tumour necrosis in H&E-stained sections was specified as an area exhibiting nuclear shrinkage, fragmentation and disappearance, and the presence of ghost-like tumour cell shadows, frequently accompanied by neutrophilic inflammatory cell infiltrate [ 19 ]. Three assessment methods, adapted from Kastinen et al [ 11 ] for colorectal cancer, were employed (Fig. 1 ). In the first method, “the average percentage method”, the average percentage of tumour necrosis relative to the tumour epithelial area was evaluated. In the second method, the “hotspot method”, a circle with a diameter of 2 mm was placed over the most necrotic hotspot, and the percentage of necrosis relative to the area of the circle was determined. Vessel structures and artefacts were excluded when assessing the proportions of necrosis. In the third method, the “linear method”, we measured the length of the single largest necrotic area. All available tumour slides were included in the assessment. The median number of slides reviewed was 3 (range 1–5). Outcomes The primary outcomes were 5-year overall survival and disease-specific survival. Overall survival was defined as the time from surgical resection to death from any cause or the last follow-up. Disease-specific survival was defined as the time from surgical resection to death specifically attributed to HCC, with deaths from other causes considered censored events. Statistical analysis Patients were first divided into two groups based on the presence of necrosis (yes/no). To assess the feasibility of the different evaluation methods, patients with any necrosis were further divided into two equally sized groups; and compared with those without necrosis. For the hotspot method, where the median was 100%, patients were divided into groups of 100% and < 100%. The cut-off scores were 5% for the average percentage method and 6000µm for the linear method. Baseline characteristics were reported as proportions, means with standard deviation (SD), and medians with interquartile range (IQR), as appropriate. Overall and disease-specific survival were compared using the Kaplan-Meier method and log-rank test. The threshold for statistical significance was set at P < 0.05. Cox regression analysis was used to evaluate long-term survival, adjusting for predetermined confounders, i.e. age (continuous), gender (male, female), Charlson comorbidity index (0–1, 2 or higher), BCLC stage (0-A, B-D), TNM stage (1, 2 or higher), cirrhosis (no, yes), year of surgery (1983–2005, 2006–2022), Child-Pugh index (A, B or C) and tumour grade (1–2, 3). All statistical analyses were performed using IBM SPSS Statistics 29.0 (IBM Corp., Armonk, NY) Results Patients A total of 96 patients were included in this cohort. The median follow-up time was 2.5 years (IQR 1.4–5.7). The median age was 69.6 years (IQR 64.5–73.6), and most patients were men (66%). The median CCI was 1.3 and most patients (82.0%) had preserved liver function (Child-Pugh class A). The median tumour size was 50 mm (IQR 31–80). Most patients (72.9%) had an early-stage disease (BCLC 0-A) and well- or moderately-differentiated tumours (88.5%). Presence of tumour necrosis Histological assessment revealed tumour necrosis in 50 (52.1%) tumours (Table 1 ). When comparing patient and tumour characteristics, the presence of tumour necrosis was significantly associated with female sex (P = 0.038), larger tumour size (P = 0.009) and higher tumour grade (P < 0.001) (Table 1 ). In patients with tumour necrosis, the 1-, 3- and 5-year overall survival rates were 84.0%, 62.0% and 50.0%, while the disease-specific survival rates were 86.0%, 70.0% and 64.0%, respectively (Fig. 2 ). For patients without necrosis, the respective 1-, 3- and 5-year overall survival rates were 95.7%, 82.6% and 76.1% and disease-specific survival rates were 97.8%, 87.0% and 82.6% (Fig. 2 ). The presence of tumour necrosis was associated with increased 5-year overall mortality (HR 2.45, 95% CI 1.21–4.98, P = 0.013) and disease-specific mortality (HR 2.41, 95% CI 1.05–5.55, P = 0.038) in univariable analysis (Table 2 ). After adjusting for confounding factors, tumour necrosis remained an independent risk factor of overall mortality (HR 2.80, 95% CI 1.26–6.22, P = 0.011) and disease-specific mortality (HR 3.89, 95% CI 1.45–10.47, P = 0.007) (Table 2 ). Tumour necrosis evaluation methods Among the 50 samples with tumour necrosis, 25 patients (50%) were classified as having a high average necrosis percentage (≥ 5%.) and a high maximal length (≥ 6000µm), while 30 patients (60%) had a high hotspot percentage (100%). The evaluation of necrosis extent showed a strong correlation between the average percentage and hotspot method (rₛ=0.63, P < 0.001), the hotspot and linear method (rₛ=0.79, P < 0.001), and the average percentage and linear method (rₛ=0.85, P < 0.001). Table 1 Baseline characteristics of patients according to tumour necrosis. Presence of necrosis Absentee (N = 46) Presentee (N = 50) P Value Age. years. Median (IQR) 68.7 (64.0-72.6) 70.8 (65.4–74.6) 0.798 Male. N (%) 35 (76.1%) 28 (56.0%) 0.038 Charlson Comorbidity Index. Mean (SD) 1.2 (0.8) 1.5 (1.0) 0.083 Cirrhosis. N (%) 22 (47.8%) 17 (34.0%) 0.168 Child-Pugh Score. N (%) A 33 (76.7%) 40 (87.0%) 0.213 B 10 (23.3%) 6 (13.0%) C 0 (0%) 0 (0%) Tumour size. mm. Median (IQR) 44 (30–60) 55 (43–100) 0.009 Unifocal tumour. N (%) 32 (69.6%) 39 (78.0%) 0.347 TNM stage. N (%) Stage 1 27 (58.7%) 32 (64.0%) 0.691 Stage 2 12 (26.1%) 11 (22.0%) Stage 3 7 (15.2%) 4 (8.0%) Stage 4 0 (0%) 3 (6.0%) BCLC stage. N (%) Very early (0) 1 (2.2%) 1 (2.0%) 0.575 Early (A) 31 (67.4%) 37 (74.0%) Intermediate (B) 11 (23.9%) 8 (16.0%) Advanced (C) 3 (6.5%) 4 (8.0%) Terminal (D) 0 (0%) 0 (0%) Tumour grade. N (%) Grade 1 24 (52.2%) 12 (24.0%) < 0.001 Grade 2 21 (45.7%) 28 (56.0%) Grade 3 1 (2.2%) 10 (20.0%) Positive resection margin. N (%) 3 (7.1%) 3 (6.4%) 0.887 AFP. Median (IQR) 5 (3–8) 10 (4-259) 0.082 Values are presented as median (IQR) or number (percentage). Baseline characteristics are compared between patients with absent and present tumour necrosis. P-values < 0.05 were considered statistically significant and are shown in bold. IQR, interquartile range; SD, standard deviation; TNM, tumour–node–metastasis; BCLC, Barcelona Clinic Liver Cancer; AFP, alpha-fetoprotein. As shown in the Kaplan–Meier curves, patients with low (but nonzero) necrosis had the worst 5-year survival across all three assessment methods, while those with higher necrosis levels showed intermediate outcomes (Fig. 3 ). In univariable analysis, a low (but nonzero) necrosis level, as assessed by the average percentage (HR 3.09, 95% CI 1.42–6.74, P = 0.005), hotspot (HR 3.15, 95% CI 1.39–7.14, P = 0.006) and linear method (HR 2.63, 95% CI 1.18–5.88, P = 0.018), were associated with increased 5-year overall mortality, compared with having no necrosis (Table 2 ). A low necrosis level according to the average percentage (HR 3.41, 95% CI 1.39–8.35, P = 0.007), hotspot (HR 3.66, 95% CI 1.44–9.28, P = 0.006) and linear method (HR 3.09, 95% CI 1.24–7.69, P = 0.015) were also associated with increased 5-year disease-specific mortality in univariable analysis (Table 2 ). In multivariable analysis, low necrosis levels according to the average percentage (HR 6.59, 95% CI 2.27–19.15, P < 0.005), hotspot (HR 8.37, 95% CI 2.47–28.34, P < 0.001) and linear method (HR 5.66, 95% CI 1.95–16.46, P = 0.001) remained an independent risk factor for 5-year overall mortality (Table 2 ). In contrast, high necrosis levels showed weaker or non-significant associations with higher mortality (Table 2 ). A low necrosis level according to the average percentage (HR 10.48, 95% CI 2.90-37.95, P < 0.001), hotspot (HR 16.14, 95% CI 3.43–75.98, P < 0.001) and linear method (HR 8.50, 95% CI 2.48–29.18, P < 0.001) were also associated with increased 5-year disease-specific mortality in multivariable analysis (Table 2 ). Table 2 Hazard ratios for overall and disease-specific mortality by tumour necrosis evaluation method Tumour necrosis a Average percentage method b Hotspot method c Linear method d Absent (N = 46) Present (N = 50) < 5% (N = 25) HR (95% CI) ≥ 5% (N = 25) HR (95% CI) < 100% (N = 20) HR (95% CI) 100% (N = 30) HR (95% CI) < 6000µm (N = 25) HR (95% CI) ≥ 6000µm (N = 25) HR (95% CI) 5-year overall mortality Crude 1.00 (reference) 2.45 (1.21–4.98; p = 0.013 ) 3.09 (1.42–6.74; p = 0.005 ) 1.37 (0.89–2.10; p = 0.152) 3.15 (1.39–7.14; p = 0.006 ) 1.43 (0.96–2.13; p = 0.083) 2.63 (1.18–5.88; p = 0.018 ) 1.51 (1.00-2.27; p = 0.049 ) Adjusted e 1.00 (reference) 2.80 (1.26–6.22; p = 0.011 ) 6.59 (2.27–19.15; p < 0.001 ) 1.71 (0.56–5.20; p = 0.346) 8.37 (2.47–28.34; p < 0.001 ) 1.76 (0.67–4.64; p = 0.255) 5.66 (1.95–16.46; p = 0.001 ) 2.11 (0.77–5.82; p = 0.148) 5-year disease-specific mortality Crude 1.00 (reference) 2.41 (1.05–5.55; p = 0.038 ) 3.41 (1.39–8.35; p = 0.007 ) 1.25 (0.73–2.12; p = 0.414) 3.66 (1.44–9.28; p = 0.006 ) 1.31 (0.80–2.14; p = 0.280) 3.09 (1.24–7.69; p = 0.015) 1.35 (0.81–2.24; p = 0.246) Adjusted e 1.00 (reference) 3.89 (1.45–10.47; p = 0.007 ) 10.48 (2.90-37.95; p < 0.001 ) 2.24 (0.44–11.31; p = 0.329) 16.14 (3.43–75.98; p < 0.001 ) 2.41 (0.68–8.56; p = 0.173) 8.50 (2.48–29.18); p < 0.001 ) 2.56 (0.66–9.95; p = 0.174) Hazard ratios (HR) with corresponding 95% confidence intervals (CI) are presented for overall and disease-specific mortality, comparing resected hepatocellular carcinoma patients according to each tumour necrosis evaluation method. P-values below 0.05 were considered statistically significant and are shown in bold. a Tumour necrosis was classified as present or absent based on the identification of necrotic tumour areas showing nuclear shrinkage, fragmentation, cell loss, and ghost-like cell outlines. b The average percentage method quantified necrosis as the proportion of necrotic tissue relative to the total tumour epithelial area. c The hotspot method assessed necrosis within a 2-mm circular region placed over the most necrotic area, excluding vessels and artefacts. d The linear method measured the length of the single largest continuous necrotic area. e Adjusted for age (continuous), sex (female, male), Charlson Comorbidity Index (0–1, 2 or higher), Barcelona Clinic Liver Cancer staging (0-A, B-D), TNM stage (1, 2 or higher), cirrhosis (no, yes), year of surgery (1983–2005, 2006–2022), Child-Pugh Index (A, B or C) and tumour grade (1–2, 3). Discussion Interestingly, lower (but nonzero) levels of necrosis were more strongly associated with a worse prognosis when compared with extensive necrosis, suggesting a complex relationship between tumour necrosis and disease progression. These findings highlight the need for further research to better understand the biological mechanisms underlying necrosis in HCC. The link between tumour necrosis and survival outcomes has been demonstrated in several prior studies for resected HCC [ 9 , 16 – 19 ]. Additionally, histological tumour necrosis has been established as a marker of poor prognosis in various solid cancers [ 11 – 15 ]. Most previous studies have focused on the prognostic significance of the presence of tumour necrosis, mainly focusing on microscopic tumour necrosis [ 9 , 11 – 18 ]. Meanwhile, macroscopic tumour necrosis [ 20 – 21 ] and radiological findings suggestive of tumour necrosis [ 22 ] has predicted worse prognosis in renal cell carcinoma. Furthermore, tumour necrosis has been incorporated into prognostic scoring systems and may improve the predictive accuracy of tumour grading systems [ 12 , 23 , 24 ]. In this study, necrosis was present in 52.1% of cases, consistent with previous HCC studies [ 9 , 16 – 19 , 23 ]. We found tumour necrosis to be associated with female sex, larger tumour size and poor tumour differentiation. While prior studies have consistently linked tumour necrosis to larger tumour size and poor differentiation, the association with female sex has not been widely reported [ 9 , 16 , 19 ]. The relationship between the extent of necrosis and long-term outcomes remains less well-defined [ 9 , 14 , 25 – 28 ]. In renal [ 26 ], upper urinary tract transitional cell carcinoma [ 27 ] and colorectal cancer [ 28 ], a linear relationship between the extent of necrosis and mortality has been observed. The percentage of necrosis has been the most commonly used method for quantification [ 9 , 14 , 19 , 25 – 28 ]. However, assessment techniques and cut-off values have varied considerably between studies, making it hard to compare results [ 9 , 14 , 19 , 25 – 28 ]. One comprehensive study evaluating tumour necrosis in colorectal cancer sought to establish standardised criteria for assessment and showed good predictive potential and reproducibility across three different evaluation methods [ 11 ]. A previous Chinese study [ 9 ] found a linear relationship between necrosis extent and mortality in HCC, whereas we found a lower proportion of necrosis to predict worse outcomes across all three assessment methods. To our knowledge, no previous studies have reported such an inverse relationship between necrosis extent and prognosis in HCC. Notably, our study exhibited a generally lower proportion of necrosis than in the Chinese cohort [ 9 ]. Differences in methodology and divergent aetiological factors could influence these differences [ 9 ]. It must be noted that they only evaluated the lesion with the most severe necrosis [ 9 ], while we assessed the mean necrosis percentage across all available tumour slides using the “average percentage method”. The linear method describes the single most necrotic area and captures the cases with the most extensive necrosis. Kastinen et al. [ 11 ] found the average percentage method to be the strongest predictor for mortality in colorectal cancer, out of the three assessment methods. Meanwhile, the hotspot method had the strongest predictive value in our study for patients with low necrosis. Given its simplicity and reproducibility, the hotspot method holds potential as a prognostic tool for evaluating necrosis extent. Tumour necrosis is frequently observed in tumours with an aggressive growth pattern, driven by metabolic stress resulting from hypoxia and nutrient deprivation [ 9 , 14 , 29 ]. In response to hypoxia, tumour cells upregulate hypoxia-inducible transcription factor, which promotes angiogenesis [ 30 ]. As tumour proliferation outpaces angiogenic capacity, ischemic areas develop, leading to necrosis [ 30 ]. The release of DAMPs from necrotic cells recruits inflammatory cells, activating transcription factors involved in cytokine and chemokine production, ultimately driving chronic inflammation and tumour progression [ 31 , 32 ]. The finding that lower levels of necrosis were associated with worse survival could be explained by differences in tumour biology at different stages of necrosis. Neutrophils attracted by chemokines in early tumour development can exhibit cytotoxic anti-tumour effects [ 33 ]; however, in the context of persistent inflammation in larger tumours, the inflammatory response from tumour cell death becomes pro-tumorigenic [ 34 ]. This may partly explain the unfavourable survival outcomes linked to a low amount of necrosis, as this group had the largest tumour size across all evaluation methods. A smaller proportion of necrosis may reflect an active phase of tumour growth, where rapidly proliferating tumour cells coexist with necrotic foci, creating a more heterogeneous and aggressive tumour microenvironment. In contrast, tumours with extensive necrosis might represent a later-stage process, where growth potential has slowed due to widespread ischemia. Additionally, inflammation-driven necrosis may generate a selective pressure favouring more aggressive and hypoxia-resistant tumour clones [ 34 ]. The larger tumour size observed in cases with low necrosis across all evaluation methods further supports this hypothesis. Assessing histological tumour necrosis is straightforward and does not require special staining techniques. Based on existing evidence, tumour necrosis holds promise as a prognostic tool for resected HCC, helping identify patients at higher risk for poor outcomes and potentially guiding adjuvant therapy. Our findings suggest that the presence of tumour necrosis, rather than its extent, might be the preferred prognostic marker in HCC. However, more studies are needed to validate the prognostic utility of the average percentage, hotspot, and linear assessment methods and to move toward a standardised approach for tumour necrosis assessment in HCC. Strengths of this study include the long follow-up period, spanning nearly 40 years, as well as the inclusion of two centres from different regions in Finland, enhancing reproducibility. However, this extended timeframe also presents limitations, as the data availability from earlier periods in the cohort was limited. Additionally, the clinical practice has evolved somewhat, with higher rates of resection in recent years. The statistical power remains limited due to the relatively small sample size and the retrospective nature of this study. The evaluation of samples by only one investigator can also be considered a weakness. In conclusion, the presence of tumour necrosis was an independent risk factor for overall and disease-specific mortality in resected HCC. However, the extent of necrosis did not correlate linearly with survival, with lower (but nonzero) levels of necrosis associated with the poorest outcomes. These findings highlight the complex role of tumour necrosis in HCC progression and underscore the need for further research to refine its prognostic value. Declarations Ethics approval and consent to participate The Ethical Committee of the North Ostrobothnia Hospital District (EETTMK 81/2008) approved the study. The study was carried out in accordance with the Declaration of Helsinki. The need to obtain informed consent from the study participants was waived by the Finnish Medicines Agency (FIMEA/2021/004928). Consent for publication Not applicable Availability of data and materials The datasets analysed during the current study are available from the corresponding author upon reasonable request. Sharing the data will require additional ethical approval. Competing interests The authors declare that they have no competing interests Funding Financial support was provided by the Mary and Georg C. Ehrnrooth Foundation, Vaasan Lääkäriyhdistys rf, and The Swedish Cultural Foundation in Finland. Authors' contributions All authors contributed to the study's conception and design. Material preparation and data collection from patient charts were performed by Niklas Sarelin, Valtteri Kairaluoma and Olli Helminen. Juha Väyrynen and Jan Böhm assisted in picking out retrieving and digitising the histological samples. Niklas Sarelin performed the histological analysis. Juha Väyrynen helped in assessing uncertain cases. The first draft of the manuscript was written by Niklas Sarelin and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. References Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71(3):209–49. Llovet JM, Kelley RK, Villanueva A, Singal AG, Pikarsky E, Roayaie S, et al. Hepatocellular carcinoma. Nat Rev Dis Primers. 2021;7(1):1–28. Guo Z, Wu D, Mao R, Yao Z, Wu Q, Lv W. Global burden of MAFLD, MAFLD related cirrhosis and MASH related liver cancer from 1990 to 2021. Sci Rep. 2025;15(1):7083. Poon RTP, Fan ST, Ng IOL, Wong J. Significance of Resection Margin in Hepatectomy for Hepatocellular Carcinoma: A Critical Reappraisal. Ann Surg. 2000;231(4):544. Galle PR, Forner A, Llovet JM, Mazzaferro V, Piscaglia F, Raoul JL, et al. EASL Clinical Practice Guidelines: Management of hepatocellular carcinoma. J Hepatol. 2018;69(1):182–236. Singal AG, Yarchoan M, Yopp A, Sapisochin G, Pinato DJ, Pillai A. Neoadjuvant and adjuvant systemic therapy in HCC: Current status and the future. Hepatol Commun. 2024;8(6):e0430. Richards CH, Mohammed Z, Qayyum T, Horgan PG, McMillan DC. The prognostic value of histological tumor necrosis in solid organ malignant disease: a systematic review. Future Oncol. 2011;7(10):1223–35. Yu LX, Ling Y, Wang HY. Role of nonresolving inflammation in hepatocellular carcinoma development and progression. NPJ Precis Oncol. 2018;2(1):6. Wei T, Zhang XF, Bagante F, Ratti F, Marques HP, Silva S, et al. Tumor Necrosis Impacts Prognosis of Patients Undergoing Curative-Intent Hepatocellular Carcinoma. Ann Surg Oncol. 2021;28(2):797–805. Chidambaranathan-Reghupaty S, Fisher PB, Sarkar D. Hepatocellular carcinoma (HCC): Epidemiology, etiology and molecular classification. Adv Cancer Res. 2020;149:1. Kastinen M, Sirniö P, Elomaa H, Ville K, Karjalainen H, Tapiainen V, et al. Establishing Criteria for Tumor Necrosis as Prognostic Indicator in Colorectal Cancer. Am J Surg Pathol. 2024;48(10):1284. Khor LY, Dhakal HP, Jia X, Reynolds JP, McKenney JK, Rini BI, et al. Tumor Necrosis Adds Prognostically Significant Information to Grade in Clear Cell Renal Cell Carcinoma: A Study of 842 Consecutive Cases From a Single Institution. Am J Surg Pathol. 2016;40(9):1224–31. Gilchrist KW, Gray R, Fowble B, Tormey DC, Taylor. SG 4th. Tumor necrosis is a prognostic predictor for early recurrence and death in lymph node-positive breast cancer. J Clin Oncol. 1993;11(10):1929–35. Swinson DEB, Jones JL, Richardson D, Cox G, Edwards JG, O’Byrne KJ. Tumour necrosis is an independent prognostic marker in non-small cell lung cancer. Lung Cancer. 2002;37(3):235–40. Hiraoka N, Ino Y, Sekine S, Tsuda H, Shimada K, Kosuge T, et al. Tumour necrosis is a postoperative prognostic marker for pancreatic cancer patients. Br J Cancer. 2010;103(7):1057–65. Atanasov G, Dino K, Schierle K, Dietel C, Aust G, Pratschke J, et al. Angiogenic inflammation and formation of necrosis in the tumor microenvironment influence survival after radical surgery for de novo hepatocellular carcinoma in non-cirrhosis. World J Surg Oncol. 2019;17(1):139659377. Ha SY, Choi S, Park S, Kim JM, Choi GS, Joh JW, et al. Prognostic effect of preoperative neutrophil-lymphocyte ratio in HCC. Virchows Arch. 2020;477(6):807–16. Ling YH, Chen JW, Wen SH, Huang CY, Li P, Lu LH et al. Tumor necrosis as a poor prognostic predictor in solitary small HCC. BMC Cancer. 2020;20(1). Wang Y, Ge H, Hu M, Pan C, Ye M, Yadav DK, et al. Histological tumor micronecrosis after R0 hepatectomy for HCC as a factor for adjuvant TACE. Int J Surg. 2022;105:106852. Pflanz S, Brookman-Amissah S, Roigas J, Kendel F, Hoschke B, May M. Impact of macroscopic tumour necrosis in renal cell carcinoma. Scand J Urol Nephrol. 2008;42(6):507–13. Lee SE, Byun SS, Oh JK, Lee SC, Chang IH, Choe G, et al. Significance of macroscopic tumor necrosis in renal cell carcinoma. J Urol. 2006;176(4):1332–8. Ooi GC, Sagar G, Lynch D, Arkell DG, Ryan PG. Cystic renal cell carcinoma: radiological and clinicopathological correlation. Clin Radiol. 1996;51(11):791–6. Yen YH, Kuo FY, Eng HL, Liu YW, Yong CC, Li WF, et al. Tumor necrosis as a predictor of early recurrence after resection in hepatoma. PLoS ONE. 2023;18(11):e0292144. Soini Y, Virkajärvi N, Lehto VP, Pääkkö P. Proliferation, apoptosis, and necrosis in hepatocellular carcinoma. Br J Cancer. 1996;73(9):1025–30. Pollheimer MJ, Kornprat P, Lindtner RA, Harbaum L, Schlemmer A, Rehak P, et al. Tumor necrosis as a prognostic factor in colorectal cancer. Hum Pathol. 2010;41(12):1749–57. Klatte T, Said JW, de Martino M, LaRochelle J, Shuch B, Rao JY, et al. Extent of tumour necrosis in renal cell carcinoma. J Urol. 2009;181(4):1558–64. Langner C, Hutterer G, Chromecki T, Leibl S, Rehak P, Zigeuner R. Tumor necrosis in upper urinary tract carcinoma. J Urol. 2006;176(3):910–4. Gao JF, Arbman G, Wadhra TI, Zhang H, Sun XF. Tumor inflammation and necrosis in colorectal cancer. World J Gastroenterol. 2005;11(14):2179–83. Leek RD, Landers RJ, Harris AL, Lewis CE. Necrosis correlates with vascular density in breast carcinoma. Br J Cancer. 1999;79(5):991–5. Wykoff CC, Beasley NJ, Watson PH, Turner KJ, Pastorek J, Sibtain A, et al. Hypoxia-inducible expression of tumor-associated carbonic anhydrases. Cancer Res. 2000;60(24):7075–83. Schwabe RF, Luedde T. Apoptosis and necroptosis in the liver. Nat Rev Gastroenterol Hepatol. 2018;15(12):738. Sharma A, Boise LH, Shanmugam M. Cancer metabolism and evasion of apoptosis. Cancers. 2019;11(8):1144. Yee PP, Wei Y, Kim SY, Lu T, Chih SY, Lawson C, et al. Neutrophil-induced ferroptosis promotes tumor necrosis in glioblastoma. Nat Commun. 2020;11(1):5424. Yee PP, Li W. Tumor necrosis: a consequence of metabolic stress and inflammation. BioEssays. 2021;43(7):e2100029. Additional Declarations No competing interests reported. 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18:05:16","extension":"xml","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":101560,"visible":true,"origin":"","legend":"","description":"","filename":"1aa34dd8d43649d185116c2eae0067de1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8134600/v1/b46549ee82400ed4cdb0a717.xml"},{"id":97672868,"identity":"2cfd0a90-8f52-49d0-9387-aaa550c6ab0d","added_by":"auto","created_at":"2025-12-08 09:38:58","extension":"html","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":108540,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8134600/v1/b67207d48b2c0d8a7530e76f.html"},{"id":97554141,"identity":"f2b1d827-20af-48bf-b999-d46fd669610b","added_by":"auto","created_at":"2025-12-05 18:05:30","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":13026737,"visible":true,"origin":"","legend":"\u003cp\u003eEvaluation methods for quantifying tumour necrosis in hepatocellular carcinoma\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Overview of the whole sample. (B) Assessment of necrosis (black areas) using the average percentage method. (C) Assessment of necrosis (black areas) using a 2 mm hotspot. Blood vessels and artefacts (red areas) were excluded when calculating necrosis in both the average percentage and hotspot methods. (D) Assessment of necrosis using the linear method, measuring the diameter of the largest continuous necrotic area.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-8134600/v1/eef413c27080e1aae5171364.png"},{"id":97671423,"identity":"ea265dac-637e-484a-a166-356dfc51bfdf","added_by":"auto","created_at":"2025-12-08 09:32:36","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2946608,"visible":true,"origin":"","legend":"\u003cp\u003eSurvival of resected hepatocellular carcinoma by tumour necrosis status.\u003c/p\u003e\n\u003cp\u003e(A) Overall survival. (B) Disease-specific survival.\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-8134600/v1/99c7af8c18162252d7394b92.png"},{"id":97554087,"identity":"4dadbb17-b7ce-4044-a95c-9b2d51b54b94","added_by":"auto","created_at":"2025-12-05 18:05:16","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":11794578,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier survival for three tumour necrosis evaluation methods.\u003c/p\u003e\n\u003cp\u003eOverall and disease-specific survival for the (A–B) average percentage method, (C–D) hotspot method, and (E–F) linear method.\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-8134600/v1/5898992f5555db2b0dd80ba6.png"},{"id":107927784,"identity":"c4f3b479-0b38-4c2e-b7ae-934bb40a5bf0","added_by":"auto","created_at":"2026-04-27 16:04:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":25582449,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8134600/v1/7da9e269-64aa-4d68-b399-825e0622d0d7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Tumour necrosis as a prognostic indicator in hepatocellular carcinoma","fulltext":[{"header":"Background","content":"\u003cp\u003eHepatocellular carcinoma (HCC) is the third leading cause of cancer-related mortality worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Chronic infection with hepatitis B and hepatitis C virus are the primary risk factors across most regions [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, metabolic dysfunction-associated fatty liver disease (MAFLD) has become the leading cause of liver cirrhosis in Western countries [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] and will consequently emerge—with a delay—as the primary cause of HCC, causing a significant disease burden that will manifest over the coming decades.\u003c/p\u003e\u003cp\u003eAlthough overall HCC management has improved, treatment strategies for surgically resectable HCC have remained largely unchanged for decades, and survival rates remain poor even after curative treatment [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. There is currently no adjuvant treatment protocol for HCC, although the recurrence rate after curative surgery is as high as 70% [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Furthermore, there is no proven benefit from neoadjuvant therapies, even though nearly 70% of newly diagnosed cases present at an advanced stage [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. This highlights the urgent need to identify biomarkers that can reliably predict tumour behaviour, recurrence risk and patient outcomes. Such biomarkers could facilitate more personalised and effective treatment strategies, guide therapeutic decision-making, and optimise treatment selection for each patient.\u003c/p\u003e\u003cp\u003eA key characteristic of HCC pathogenesis is the role of persistent inflammation in the hepatic parenchyma [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Hepatocytes are damaged by various exogenous factors, leading to the release of molecular mediators like Damage-Associated Molecular Patterns (DAMPs) from dying liver cells [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. This allows the host to respond to cell death through specific DAMP receptors, creating a local and systemic inflammatory response [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Persistent inflammation and cell death can result in progressive liver fibrosis and, culminating in cirrhosis, which is present in approximately 80–90% of HCC cases [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Furthermore, the aggressive tumour growth coupled with compromised oxygen delivery leads to tumour necrosis in a subset of HCC [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Tumour necrosis has been associated with poor prognosis in various solid cancers, including colorectal [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], renal [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], breast [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], lung [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] and pancreatic cancer [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], as well as HCC [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan additionalcitationids=\"CR17 CR18\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e–\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTumour necrosis holds promise as a prognostic biomarker in HCC. Importantly, it can be analysed from haematoxylin- and eosin (H\u0026amp;E)-stained samples without complex or costly methods. However, the optimal approach for quantifying tumour necrosis in HCC remains inadequately defined [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan additionalcitationids=\"CR17 CR18\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e–\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. While comparative studies have been conducted in some other malignancies, such as colorectal cancer [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], there is a lack of consensus on standardised assessment methods specific to HCC [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOur study aimed to determine the independent prognostic role of tumour necrosis in a bi-institutional cohort of HCC patients. Additionally, we sought to evaluate and compare methods for quantifying tumour necrosis in HCC.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003ePatient cohort\u003c/p\u003e\u003cp\u003eA total of 99 HCC patients who were suitable for surgical resection were identified. Patients were diagnosed at Oulu University Hospital from 1986 to 2022 and at Central Finland Central Hospital from 1997 to 2022. Only histologically confirmed cases were included. Those who received neoadjuvant therapies (N = 3) were excluded, resulting in a final cohort of 96 patients. The study received approval from the Finnish Medicines Agency Fimea (Dnro FIMEA/2021/004928) and the Ethical Committee of the North Ostrobothnia Hospital District (EETTMK 81/2008). The study was conducted in accordance with the Declaration of Helsinki.\u003c/p\u003e\u003cp\u003eData collection\u003c/p\u003e\u003cp\u003eWe identified patients from the pathology archives using the ICD-10 code C22.0\u0026amp;. Relevant clinical information was collected from the patient charts and pathology reports. The 8th edition of the TNM classification was used for staging. Comorbidities were assessed using the Charlson Comorbidity Index (CCI), and postoperative complications were classified according to the Clavien-Dindo classification system. Cause of death and date of death were obtained from Statistics Finland. Follow-up data was gathered up to the end of 2022.\u003c/p\u003e\u003cp\u003eDiagnostic H\u0026amp;E-stained tumour slides were retrieved from pathology archives and digitised using Aperio AT2 (Leica Biosystems, Wetzlar, Germany). The tumour grade was evaluated by a pathologist (J.P.V.) when it was not documented in the original pathology report. Tumour necrosis was analysed by one researcher (N.S.) using Aperio ImageScope. A second investigator (J.P.V.) assessed uncertain cases.\u003c/p\u003e\u003cp\u003eHistopathological examination\u003c/p\u003e\u003cp\u003eTumour necrosis in H\u0026amp;E-stained sections was specified as an area exhibiting nuclear shrinkage, fragmentation and disappearance, and the presence of ghost-like tumour cell shadows, frequently accompanied by neutrophilic inflammatory cell infiltrate [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Three assessment methods, adapted from Kastinen et al [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] for colorectal cancer, were employed (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In the first method, “the average percentage method”, the average percentage of tumour necrosis relative to the tumour epithelial area was evaluated. In the second method, the “hotspot method”, a circle with a diameter of 2 mm was placed over the most necrotic hotspot, and the percentage of necrosis relative to the area of the circle was determined. Vessel structures and artefacts were excluded when assessing the proportions of necrosis. In the third method, the “linear method”, we measured the length of the single largest necrotic area. All available tumour slides were included in the assessment. The median number of slides reviewed was 3 (range 1–5).\u003c/p\u003e\u003cp\u003eOutcomes\u003c/p\u003e\u003cp\u003eThe primary outcomes were 5-year overall survival and disease-specific survival. Overall survival was defined as the time from surgical resection to death from any cause or the last follow-up. Disease-specific survival was defined as the time from surgical resection to death specifically attributed to HCC, with deaths from other causes considered censored events.\u003c/p\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003ePatients were first divided into two groups based on the presence of necrosis (yes/no). To assess the feasibility of the different evaluation methods, patients with any necrosis were further divided into two equally sized groups; and compared with those without necrosis. For the hotspot method, where the median was 100%, patients were divided into groups of 100% and \u0026lt; 100%. The cut-off scores were 5% for the average percentage method and 6000µm for the linear method.\u003c/p\u003e\u003cp\u003eBaseline characteristics were reported as proportions, means with standard deviation (SD), and medians with interquartile range (IQR), as appropriate. Overall and disease-specific survival were compared using the Kaplan-Meier method and log-rank test. The threshold for statistical significance was set at P \u0026lt; 0.05. Cox regression analysis was used to evaluate long-term survival, adjusting for predetermined confounders, i.e. age (continuous), gender (male, female), Charlson comorbidity index (0–1, 2 or higher), BCLC stage (0-A, B-D), TNM stage (1, 2 or higher), cirrhosis (no, yes), year of surgery (1983–2005, 2006–2022), Child-Pugh index (A, B or C) and tumour grade (1–2, 3). All statistical analyses were performed using IBM SPSS Statistics 29.0 (IBM Corp., Armonk, NY)\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003ePatients\u003c/p\u003e\u003cp\u003eA total of 96 patients were included in this cohort. The median follow-up time was 2.5 years (IQR 1.4\u0026ndash;5.7). The median age was 69.6 years (IQR 64.5\u0026ndash;73.6), and most patients were men (66%). The median CCI was 1.3 and most patients (82.0%) had preserved liver function (Child-Pugh class A). The median tumour size was 50 mm (IQR 31\u0026ndash;80). Most patients (72.9%) had an early-stage disease (BCLC 0-A) and well- or moderately-differentiated tumours (88.5%).\u003c/p\u003e\u003cp\u003ePresence of tumour necrosis\u003c/p\u003e\u003cp\u003eHistological assessment revealed tumour necrosis in 50 (52.1%) tumours (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). When comparing patient and tumour characteristics, the presence of tumour necrosis was significantly associated with female sex (P\u0026thinsp;=\u0026thinsp;0.038), larger tumour size (P\u0026thinsp;=\u0026thinsp;0.009) and higher tumour grade (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn patients with tumour necrosis, the 1-, 3- and 5-year overall survival rates were 84.0%, 62.0% and 50.0%, while the disease-specific survival rates were 86.0%, 70.0% and 64.0%, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). For patients without necrosis, the respective 1-, 3- and 5-year overall survival rates were 95.7%, 82.6% and 76.1% and disease-specific survival rates were 97.8%, 87.0% and 82.6% (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The presence of tumour necrosis was associated with increased 5-year overall mortality (HR 2.45, 95% CI 1.21\u0026ndash;4.98, P\u0026thinsp;=\u0026thinsp;0.013) and disease-specific mortality (HR 2.41, 95% CI 1.05\u0026ndash;5.55, P\u0026thinsp;=\u0026thinsp;0.038) in univariable analysis (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). After adjusting for confounding factors, tumour necrosis remained an independent risk factor of overall mortality (HR 2.80, 95% CI 1.26\u0026ndash;6.22, P\u0026thinsp;=\u0026thinsp;0.011) and disease-specific mortality (HR 3.89, 95% CI 1.45\u0026ndash;10.47, P\u0026thinsp;=\u0026thinsp;0.007) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTumour necrosis evaluation methods\u003c/p\u003e\u003cp\u003eAmong the 50 samples with tumour necrosis, 25 patients (50%) were classified as having a high average necrosis percentage (\u0026ge;\u0026thinsp;5%.) and a high maximal length (\u0026ge;\u0026thinsp;6000\u0026micro;m), while 30 patients (60%) had a high hotspot percentage (100%). The evaluation of necrosis extent showed a strong correlation between the average percentage and hotspot method (rₛ=0.63, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), the hotspot and linear method (rₛ=0.79, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and the average percentage and linear method (rₛ=0.85, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBaseline characteristics of patients according to tumour necrosis.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003ePresence of necrosis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAbsentee (N\u0026thinsp;=\u0026thinsp;46)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePresentee (N\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP Value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eAge. years. Median (IQR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e68.7 (64.0-72.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e70.8 (65.4\u0026ndash;74.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.798\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eMale. N (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35 (76.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28 (56.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.038\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eCharlson Comorbidity Index. Mean (SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.2 (0.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.5 (1.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.083\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eCirrhosis. N (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22 (47.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17 (34.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.168\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eChild-Pugh Score. N (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33 (76.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e40 (87.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.213\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10 (23.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (13.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eTumour size. mm. Median (IQR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e44 (30\u0026ndash;60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e55 (43\u0026ndash;100)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eUnifocal tumour. N (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e32 (69.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e39 (78.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.347\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eTNM stage. N (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStage 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27 (58.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32 (64.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.691\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStage 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12 (26.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11 (22.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStage 3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7 (15.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (8.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStage 4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (6.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eBCLC stage. N (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVery early (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (2.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (2.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e0.575\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEarly (A)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e31 (67.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37 (74.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIntermediate (B)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11 (23.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8 (16.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAdvanced (C)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (6.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (8.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTerminal (D)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eTumour grade. N (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGrade 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24 (52.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12 (24.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGrade 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21 (45.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28 (56.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGrade 3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (2.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 (20.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003ePositive resection margin. N (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (7.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (6.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.887\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eAFP. Median (IQR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5 (3\u0026ndash;8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 (4-259)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.082\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eValues are presented as median (IQR) or number (percentage). Baseline characteristics are compared between patients with absent and present tumour necrosis. P-values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered statistically significant and are shown in bold.\u003c/p\u003e\u003cp\u003eIQR, interquartile range; SD, standard deviation; TNM, tumour\u0026ndash;node\u0026ndash;metastasis; BCLC, Barcelona Clinic Liver Cancer; AFP, alpha-fetoprotein.\u003c/p\u003e\u003cp\u003eAs shown in the Kaplan\u0026ndash;Meier curves, patients with low (but nonzero) necrosis had the worst 5-year survival across all three assessment methods, while those with higher necrosis levels showed intermediate outcomes (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In univariable analysis, a low (but nonzero) necrosis level, as assessed by the average percentage (HR 3.09, 95% CI 1.42\u0026ndash;6.74, P\u0026thinsp;=\u0026thinsp;0.005), hotspot (HR 3.15, 95% CI 1.39\u0026ndash;7.14, P\u0026thinsp;=\u0026thinsp;0.006) and linear method (HR 2.63, 95% CI 1.18\u0026ndash;5.88, P\u0026thinsp;=\u0026thinsp;0.018), were associated with increased 5-year overall mortality, compared with having no necrosis (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). A low necrosis level according to the average percentage (HR 3.41, 95% CI 1.39\u0026ndash;8.35, P\u0026thinsp;=\u0026thinsp;0.007), hotspot (HR 3.66, 95% CI 1.44\u0026ndash;9.28, P\u0026thinsp;=\u0026thinsp;0.006) and linear method (HR 3.09, 95% CI 1.24\u0026ndash;7.69, P\u0026thinsp;=\u0026thinsp;0.015) were also associated with increased 5-year disease-specific mortality in univariable analysis (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In multivariable analysis, low necrosis levels according to the average percentage (HR 6.59, 95% CI 2.27\u0026ndash;19.15, P\u0026thinsp;\u0026lt;\u0026thinsp;0.005), hotspot (HR 8.37, 95% CI 2.47\u0026ndash;28.34, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and linear method (HR 5.66, 95% CI 1.95\u0026ndash;16.46, P\u0026thinsp;=\u0026thinsp;0.001) remained an independent risk factor for 5-year overall mortality (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In contrast, high necrosis levels showed weaker or non-significant associations with higher mortality (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). A low necrosis level according to the average percentage (HR 10.48, 95% CI 2.90-37.95, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), hotspot (HR 16.14, 95% CI 3.43\u0026ndash;75.98, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and linear method (HR 8.50, 95% CI 2.48\u0026ndash;29.18, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were also associated with increased 5-year disease-specific mortality in multivariable analysis (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eHazard ratios for overall and disease-specific mortality by tumour necrosis evaluation method\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eTumour necrosis\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eAverage percentage method\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eHotspot method\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003eLinear method\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAbsent (N\u0026thinsp;=\u0026thinsp;46)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePresent (N\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;5% (N\u0026thinsp;=\u0026thinsp;25)\u003c/p\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;5% (N\u0026thinsp;=\u0026thinsp;25)\u003c/p\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;100% (N\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e\u003cp\u003eHR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e100% (N\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e\u003cp\u003eHR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;6000\u0026micro;m (N\u0026thinsp;=\u0026thinsp;25)\u003c/p\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;6000\u0026micro;m (N\u0026thinsp;=\u0026thinsp;25)\u003c/p\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e\u003cp\u003e5-year overall mortality\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCrude\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.00 (reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.45 (1.21\u0026ndash;4.98; \u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.013\u003c/b\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.09 (1.42\u0026ndash;6.74; \u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.005\u003c/b\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.37 (0.89\u0026ndash;2.10; p\u0026thinsp;=\u0026thinsp;0.152)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.15 (1.39\u0026ndash;7.14; \u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.006\u003c/b\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.43 (0.96\u0026ndash;2.13; p\u0026thinsp;=\u0026thinsp;0.083)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.63 (1.18\u0026ndash;5.88; \u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.018\u003c/b\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1.51 (1.00-2.27; \u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.049\u003c/b\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdjusted\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.00 (reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.80 (1.26\u0026ndash;6.22; \u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.011\u003c/b\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.59 (2.27\u0026ndash;19.15; \u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/b\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.71 (0.56\u0026ndash;5.20; p\u0026thinsp;=\u0026thinsp;0.346)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8.37 (2.47\u0026ndash;28.34; \u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/b\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.76 (0.67\u0026ndash;4.64; p\u0026thinsp;=\u0026thinsp;0.255)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e5.66 (1.95\u0026ndash;16.46; \u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.001\u003c/b\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e2.11 (0.77\u0026ndash;5.82; p\u0026thinsp;=\u0026thinsp;0.148)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e\u003cp\u003e5-year disease-specific mortality\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCrude\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.00 (reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.41 (1.05\u0026ndash;5.55; \u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.038\u003c/b\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.41 (1.39\u0026ndash;8.35; \u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.007\u003c/b\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.25 (0.73\u0026ndash;2.12; p\u0026thinsp;=\u0026thinsp;0.414)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.66 (1.44\u0026ndash;9.28; \u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.006\u003c/b\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.31 (0.80\u0026ndash;2.14; p\u0026thinsp;=\u0026thinsp;0.280)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.09 (1.24\u0026ndash;7.69; p\u0026thinsp;=\u0026thinsp;0.015)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1.35 (0.81\u0026ndash;2.24; p\u0026thinsp;=\u0026thinsp;0.246)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdjusted\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.00 (reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.89 (1.45\u0026ndash;10.47; \u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.007\u003c/b\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.48 (2.90-37.95; \u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/b\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.24 (0.44\u0026ndash;11.31; p\u0026thinsp;=\u0026thinsp;0.329)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e16.14 (3.43\u0026ndash;75.98; \u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/b\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.41 (0.68\u0026ndash;8.56; p\u0026thinsp;=\u0026thinsp;0.173)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e8.50 (2.48\u0026ndash;29.18); \u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/b\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e2.56 (0.66\u0026ndash;9.95; p\u0026thinsp;=\u0026thinsp;0.174)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eHazard ratios (HR) with corresponding 95% confidence intervals (CI) are presented for overall and disease-specific mortality, comparing resected hepatocellular carcinoma patients according to each tumour necrosis evaluation method. P-values below 0.05 were considered statistically significant and are shown in bold.\u003c/p\u003e\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eTumour necrosis was classified as present or absent based on the identification of necrotic tumour areas showing nuclear shrinkage, fragmentation, cell loss, and ghost-like cell outlines.\u003c/p\u003e\u003cp\u003e\u003csup\u003eb\u003c/sup\u003eThe average percentage method quantified necrosis as the proportion of necrotic tissue relative to the total tumour epithelial area.\u003c/p\u003e\u003cp\u003e\u003csup\u003ec\u003c/sup\u003eThe hotspot method assessed necrosis within a 2-mm circular region placed over the most necrotic area, excluding vessels and artefacts.\u003c/p\u003e\u003cp\u003e\u003csup\u003ed\u003c/sup\u003eThe linear method measured the length of the single largest continuous necrotic area.\u003c/p\u003e\u003cp\u003e\u003csup\u003ee\u003c/sup\u003eAdjusted for age (continuous), sex (female, male), Charlson Comorbidity Index (0\u0026ndash;1, 2 or higher), Barcelona Clinic Liver Cancer staging (0-A, B-D), TNM stage (1, 2 or higher), cirrhosis (no, yes), year of surgery (1983\u0026ndash;2005, 2006\u0026ndash;2022), Child-Pugh Index (A, B or C) and tumour grade (1\u0026ndash;2, 3).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eInterestingly, lower (but nonzero) levels of necrosis were more strongly associated with a worse prognosis when compared with extensive necrosis, suggesting a complex relationship between tumour necrosis and disease progression. These findings highlight the need for further research to better understand the biological mechanisms underlying necrosis in HCC.\u003c/p\u003e\u003cp\u003eThe link between tumour necrosis and survival outcomes has been demonstrated in several prior studies for resected HCC [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan additionalcitationids=\"CR17 CR18\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Additionally, histological tumour necrosis has been established as a marker of poor prognosis in various solid cancers [\u003cspan additionalcitationids=\"CR12 CR13 CR14\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Most previous studies have focused on the prognostic significance of the presence of tumour necrosis, mainly focusing on microscopic tumour necrosis [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan additionalcitationids=\"CR12 CR13 CR14 CR15 CR16 CR17\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Meanwhile, macroscopic tumour necrosis [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] and radiological findings suggestive of tumour necrosis [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] has predicted worse prognosis in renal cell carcinoma. Furthermore, tumour necrosis has been incorporated into prognostic scoring systems and may improve the predictive accuracy of tumour grading systems [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In this study, necrosis was present in 52.1% of cases, consistent with previous HCC studies [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan additionalcitationids=\"CR17 CR18\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. We found tumour necrosis to be associated with female sex, larger tumour size and poor tumour differentiation. While prior studies have consistently linked tumour necrosis to larger tumour size and poor differentiation, the association with female sex has not been widely reported [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe relationship between the extent of necrosis and long-term outcomes remains less well-defined [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan additionalcitationids=\"CR26 CR27\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. In renal [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], upper urinary tract transitional cell carcinoma [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] and colorectal cancer [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], a linear relationship between the extent of necrosis and mortality has been observed. The percentage of necrosis has been the most commonly used method for quantification [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan additionalcitationids=\"CR26 CR27\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. However, assessment techniques and cut-off values have varied considerably between studies, making it hard to compare results [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan additionalcitationids=\"CR26 CR27\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. One comprehensive study evaluating tumour necrosis in colorectal cancer sought to establish standardised criteria for assessment and showed good predictive potential and reproducibility across three different evaluation methods [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eA previous Chinese study [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] found a linear relationship between necrosis extent and mortality in HCC, whereas we found a lower proportion of necrosis to predict worse outcomes across all three assessment methods. To our knowledge, no previous studies have reported such an inverse relationship between necrosis extent and prognosis in HCC. Notably, our study exhibited a generally lower proportion of necrosis than in the Chinese cohort [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Differences in methodology and divergent aetiological factors could influence these differences [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. It must be noted that they only evaluated the lesion with the most severe necrosis [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], while we assessed the mean necrosis percentage across all available tumour slides using the \u0026ldquo;average percentage method\u0026rdquo;. The linear method describes the single most necrotic area and captures the cases with the most extensive necrosis. Kastinen et al. [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] found the average percentage method to be the strongest predictor for mortality in colorectal cancer, out of the three assessment methods. Meanwhile, the hotspot method had the strongest predictive value in our study for patients with low necrosis. Given its simplicity and reproducibility, the hotspot method holds potential as a prognostic tool for evaluating necrosis extent.\u003c/p\u003e\u003cp\u003eTumour necrosis is frequently observed in tumours with an aggressive growth pattern, driven by metabolic stress resulting from hypoxia and nutrient deprivation [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. In response to hypoxia, tumour cells upregulate hypoxia-inducible transcription factor, which promotes angiogenesis [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. As tumour proliferation outpaces angiogenic capacity, ischemic areas develop, leading to necrosis [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The release of DAMPs from necrotic cells recruits inflammatory cells, activating transcription factors involved in cytokine and chemokine production, ultimately driving chronic inflammation and tumour progression [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe finding that lower levels of necrosis were associated with worse survival could be explained by differences in tumour biology at different stages of necrosis. Neutrophils attracted by chemokines in early tumour development can exhibit cytotoxic anti-tumour effects [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]; however, in the context of persistent inflammation in larger tumours, the inflammatory response from tumour cell death becomes pro-tumorigenic [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. This may partly explain the unfavourable survival outcomes linked to a low amount of necrosis, as this group had the largest tumour size across all evaluation methods. A smaller proportion of necrosis may reflect an active phase of tumour growth, where rapidly proliferating tumour cells coexist with necrotic foci, creating a more heterogeneous and aggressive tumour microenvironment. In contrast, tumours with extensive necrosis might represent a later-stage process, where growth potential has slowed due to widespread ischemia. Additionally, inflammation-driven necrosis may generate a selective pressure favouring more aggressive and hypoxia-resistant tumour clones [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The larger tumour size observed in cases with low necrosis across all evaluation methods further supports this hypothesis.\u003c/p\u003e\u003cp\u003eAssessing histological tumour necrosis is straightforward and does not require special staining techniques. Based on existing evidence, tumour necrosis holds promise as a prognostic tool for resected HCC, helping identify patients at higher risk for poor outcomes and potentially guiding adjuvant therapy. Our findings suggest that the presence of tumour necrosis, rather than its extent, might be the preferred prognostic marker in HCC. However, more studies are needed to validate the prognostic utility of the average percentage, hotspot, and linear assessment methods and to move toward a standardised approach for tumour necrosis assessment in HCC.\u003c/p\u003e\u003cp\u003eStrengths of this study include the long follow-up period, spanning nearly 40 years, as well as the inclusion of two centres from different regions in Finland, enhancing reproducibility. However, this extended timeframe also presents limitations, as the data availability from earlier periods in the cohort was limited. Additionally, the clinical practice has evolved somewhat, with higher rates of resection in recent years. The statistical power remains limited due to the relatively small sample size and the retrospective nature of this study. The evaluation of samples by only one investigator can also be considered a weakness.\u003c/p\u003e\u003cp\u003eIn conclusion, the presence of tumour necrosis was an independent risk factor for overall and disease-specific mortality in resected HCC. However, the extent of necrosis did not correlate linearly with survival, with lower (but nonzero) levels of necrosis associated with the poorest outcomes. These findings highlight the complex role of tumour necrosis in HCC progression and underscore the need for further research to refine its prognostic value.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Ethical Committee of the North Ostrobothnia Hospital District (EETTMK 81/2008) approved the study. The study was carried out in accordance with the Declaration of Helsinki. The need to obtain informed consent from the study participants was waived by the Finnish Medicines Agency (FIMEA/2021/004928).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets analysed during the current study are available from the corresponding author upon reasonable request. Sharing the data will require additional ethical approval.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFinancial support was provided by the Mary and Georg C. Ehrnrooth Foundation, Vaasan L\u0026auml;\u0026auml;k\u0026auml;riyhdistys rf, and The Swedish Cultural Foundation in Finland.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study\u0026apos;s conception and design. Material preparation and data collection from patient charts were performed by Niklas Sarelin, Valtteri Kairaluoma and Olli Helminen. Juha V\u0026auml;yrynen and Jan B\u0026ouml;hm assisted in picking out retrieving and digitising the histological samples. Niklas Sarelin performed the histological analysis. Juha V\u0026auml;yrynen helped in assessing uncertain cases. The first draft of the manuscript was written by Niklas Sarelin and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71(3):209\u0026ndash;49.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLlovet JM, Kelley RK, Villanueva A, Singal AG, Pikarsky E, Roayaie S, et al. Hepatocellular carcinoma. Nat Rev Dis Primers. 2021;7(1):1\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGuo Z, Wu D, Mao R, Yao Z, Wu Q, Lv W. Global burden of MAFLD, MAFLD related cirrhosis and MASH related liver cancer from 1990 to 2021. Sci Rep. 2025;15(1):7083.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePoon RTP, Fan ST, Ng IOL, Wong J. Significance of Resection Margin in Hepatectomy for Hepatocellular Carcinoma: A Critical Reappraisal. Ann Surg. 2000;231(4):544.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGalle PR, Forner A, Llovet JM, Mazzaferro V, Piscaglia F, Raoul JL, et al. EASL Clinical Practice Guidelines: Management of hepatocellular carcinoma. J Hepatol. 2018;69(1):182\u0026ndash;236.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSingal AG, Yarchoan M, Yopp A, Sapisochin G, Pinato DJ, Pillai A. Neoadjuvant and adjuvant systemic therapy in HCC: Current status and the future. Hepatol Commun. 2024;8(6):e0430.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRichards CH, Mohammed Z, Qayyum T, Horgan PG, McMillan DC. The prognostic value of histological tumor necrosis in solid organ malignant disease: a systematic review. Future Oncol. 2011;7(10):1223\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYu LX, Ling Y, Wang HY. Role of nonresolving inflammation in hepatocellular carcinoma development and progression. NPJ Precis Oncol. 2018;2(1):6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWei T, Zhang XF, Bagante F, Ratti F, Marques HP, Silva S, et al. Tumor Necrosis Impacts Prognosis of Patients Undergoing Curative-Intent Hepatocellular Carcinoma. Ann Surg Oncol. 2021;28(2):797\u0026ndash;805.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChidambaranathan-Reghupaty S, Fisher PB, Sarkar D. Hepatocellular carcinoma (HCC): Epidemiology, etiology and molecular classification. Adv Cancer Res. 2020;149:1.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKastinen M, Sirni\u0026ouml; P, Elomaa H, Ville K, Karjalainen H, Tapiainen V, et al. Establishing Criteria for Tumor Necrosis as Prognostic Indicator in Colorectal Cancer. Am J Surg Pathol. 2024;48(10):1284.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKhor LY, Dhakal HP, Jia X, Reynolds JP, McKenney JK, Rini BI, et al. Tumor Necrosis Adds Prognostically Significant Information to Grade in Clear Cell Renal Cell Carcinoma: A Study of 842 Consecutive Cases From a Single Institution. Am J Surg Pathol. 2016;40(9):1224\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGilchrist KW, Gray R, Fowble B, Tormey DC, Taylor. SG 4th. Tumor necrosis is a prognostic predictor for early recurrence and death in lymph node-positive breast cancer. J Clin Oncol. 1993;11(10):1929\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSwinson DEB, Jones JL, Richardson D, Cox G, Edwards JG, O\u0026rsquo;Byrne KJ. Tumour necrosis is an independent prognostic marker in non-small cell lung cancer. Lung Cancer. 2002;37(3):235\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHiraoka N, Ino Y, Sekine S, Tsuda H, Shimada K, Kosuge T, et al. Tumour necrosis is a postoperative prognostic marker for pancreatic cancer patients. Br J Cancer. 2010;103(7):1057\u0026ndash;65.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAtanasov G, Dino K, Schierle K, Dietel C, Aust G, Pratschke J, et al. Angiogenic inflammation and formation of necrosis in the tumor microenvironment influence survival after radical surgery for de novo hepatocellular carcinoma in non-cirrhosis. World J Surg Oncol. 2019;17(1):139659377.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHa SY, Choi S, Park S, Kim JM, Choi GS, Joh JW, et al. Prognostic effect of preoperative neutrophil-lymphocyte ratio in HCC. Virchows Arch. 2020;477(6):807\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLing YH, Chen JW, Wen SH, Huang CY, Li P, Lu LH et al. Tumor necrosis as a poor prognostic predictor in solitary small HCC. BMC Cancer. 2020;20(1).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang Y, Ge H, Hu M, Pan C, Ye M, Yadav DK, et al. Histological tumor micronecrosis after R0 hepatectomy for HCC as a factor for adjuvant TACE. Int J Surg. 2022;105:106852.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePflanz S, Brookman-Amissah S, Roigas J, Kendel F, Hoschke B, May M. Impact of macroscopic tumour necrosis in renal cell carcinoma. Scand J Urol Nephrol. 2008;42(6):507\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLee SE, Byun SS, Oh JK, Lee SC, Chang IH, Choe G, et al. Significance of macroscopic tumor necrosis in renal cell carcinoma. J Urol. 2006;176(4):1332\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOoi GC, Sagar G, Lynch D, Arkell DG, Ryan PG. Cystic renal cell carcinoma: radiological and clinicopathological correlation. Clin Radiol. 1996;51(11):791\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYen YH, Kuo FY, Eng HL, Liu YW, Yong CC, Li WF, et al. Tumor necrosis as a predictor of early recurrence after resection in hepatoma. PLoS ONE. 2023;18(11):e0292144.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSoini Y, Virkaj\u0026auml;rvi N, Lehto VP, P\u0026auml;\u0026auml;kk\u0026ouml; P. Proliferation, apoptosis, and necrosis in hepatocellular carcinoma. Br J Cancer. 1996;73(9):1025\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePollheimer MJ, Kornprat P, Lindtner RA, Harbaum L, Schlemmer A, Rehak P, et al. Tumor necrosis as a prognostic factor in colorectal cancer. Hum Pathol. 2010;41(12):1749\u0026ndash;57.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKlatte T, Said JW, de Martino M, LaRochelle J, Shuch B, Rao JY, et al. Extent of tumour necrosis in renal cell carcinoma. J Urol. 2009;181(4):1558\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLangner C, Hutterer G, Chromecki T, Leibl S, Rehak P, Zigeuner R. Tumor necrosis in upper urinary tract carcinoma. J Urol. 2006;176(3):910\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGao JF, Arbman G, Wadhra TI, Zhang H, Sun XF. Tumor inflammation and necrosis in colorectal cancer. World J Gastroenterol. 2005;11(14):2179\u0026ndash;83.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLeek RD, Landers RJ, Harris AL, Lewis CE. Necrosis correlates with vascular density in breast carcinoma. Br J Cancer. 1999;79(5):991\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWykoff CC, Beasley NJ, Watson PH, Turner KJ, Pastorek J, Sibtain A, et al. Hypoxia-inducible expression of tumor-associated carbonic anhydrases. Cancer Res. 2000;60(24):7075\u0026ndash;83.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchwabe RF, Luedde T. Apoptosis and necroptosis in the liver. Nat Rev Gastroenterol Hepatol. 2018;15(12):738.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSharma A, Boise LH, Shanmugam M. Cancer metabolism and evasion of apoptosis. Cancers. 2019;11(8):1144.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYee PP, Wei Y, Kim SY, Lu T, Chih SY, Lawson C, et al. Neutrophil-induced ferroptosis promotes tumor necrosis in glioblastoma. Nat Commun. 2020;11(1):5424.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYee PP, Li W. Tumor necrosis: a consequence of metabolic stress and inflammation. BioEssays. 2021;43(7):e2100029.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Hepatocellular carcinoma, Surgical resection, Prognostic biomarker, Tumour necrosis","lastPublishedDoi":"10.21203/rs.3.rs-8134600/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8134600/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eTumour necrosis is linked to worse outcomes in hepatocellular carcinoma (HCC). However, the relationship between the extent of necrosis in HCC and survival outcomes remains unclear, partly due to the lack of a standardised assessment method. This study analysed the prognostic significance of tumour necrosis and compared three quantification methods.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis retrospective study included 96 HCC patients from two Finnish centres, treated with surgical resection from 1986 to 2022. The extent of necrosis was assessed using three methods: (1) The average percentage method (proportion of necrosis relative to total tumour area), (2) the hotspot method (proportion of necrosis within a 2 mm hotspot), and (3) the linear method (diameter of the largest necrotic focus).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eTumour necrosis was an independent risk factor for 5-year overall (HR 2.80, 95% CI 1.26\u0026ndash;6.22, P\u0026thinsp;=\u0026thinsp;0.011) and disease-specific mortality (HR 3.89, 95% CI 1.45\u0026ndash;10.47, P\u0026thinsp;=\u0026thinsp;0.007). Tumours with low (but nonzero) necrosis level, as measured by the average percentage, hotspot, and linear methods, were linked to poorer 5-year overall and disease-specific survival compared to tumours without necrosis.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eTumour necrosis is an independent risk factor for overall and disease-specific mortality in resected HCC. Lower (but nonzero) levels of necrosis were more strongly associated with a worse prognosis when compared with extensive necrosis, suggesting a complex relationship between tumour necrosis and disease progression.\u003c/p\u003e","manuscriptTitle":"Tumour necrosis as a prognostic indicator in hepatocellular carcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-05 18:05:10","doi":"10.21203/rs.3.rs-8134600/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-02T16:56:42+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-27T11:06:00+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-18T08:26:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"252124101279250166246440720615408895404","date":"2025-12-15T22:41:23+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-15T20:33:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"322078067563033365577418729848381520281","date":"2025-12-15T13:37:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"322418769927766034153066744005518403702","date":"2025-12-13T19:23:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"12456988592027281806380121401304115952","date":"2025-12-13T13:45:51+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-13T11:23:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"328999732767517248970905887785114468270","date":"2025-12-13T04:47:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"79764465021702819921378902718431466202","date":"2025-12-13T04:24:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"21006172996339097515048933471900963243","date":"2025-12-12T20:46:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"94309203399622556845578467347303536720","date":"2025-12-12T18:12:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"92999861012884579127560687701092777023","date":"2025-12-06T08:07:26+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-04T03:30:56+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-25T08:00:44+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-25T04:52:56+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-24T19:02:21+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2025-11-24T18:59:05+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0bca189b-d96a-424a-bf00-e7ef7aa5b1e4","owner":[],"postedDate":"December 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-04-27T16:02:05+00:00","versionOfRecord":{"articleIdentity":"rs-8134600","link":"https://doi.org/10.1186/s12885-026-16040-z","journal":{"identity":"bmc-cancer","isVorOnly":false,"title":"BMC Cancer"},"publishedOn":"2026-04-21 15:57:20","publishedOnDateReadable":"April 21st, 2026"},"versionCreatedAt":"2025-12-05 18:05:10","video":"","vorDoi":"10.1186/s12885-026-16040-z","vorDoiUrl":"https://doi.org/10.1186/s12885-026-16040-z","workflowStages":[]},"version":"v1","identity":"rs-8134600","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8134600","identity":"rs-8134600","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}