Background
Hepatocellular carcinoma (HCC) is the third most common cause of cancer death in the world and accounts for over 500,000 deaths a year [
1]. HCC is a unique type of cancer, which mostly arises in livers with chronic necroinflammatory damage due to various etiologies such as hepatitis C virus infection and non-alcoholic steatohepatitis [
2]. Because long lasting necroinflammation leads to reductions of functional liver reserves, the patient’s survival cannot be predicted from cancer stage alone, which is done in the other types of cancer. It has been reported that a system integrating both cancer stage and functional liver reserve can accurately stratify patient survival rates [
3]. For example, the Japan integrating scoring indicates that the functional liver reserve as assessed by the Child-Pugh scoring system has an impact on a patients’ survival equivalent to anatomical cancer extension [
4]. Thus, it is advisable to manage functional liver reserves in HCC patients in parallel with their cancer treatment in order to improve survival.
In terms of nutritional state, a characteristic feature of patients suffering from liver cirrhosis is protein-energy malnutrition (PEM) [
5,
6]. An insufficient energy intake of less than 30 kcal/kg has been reported to be associated with a poor prognosis in cases of liver cirrhosis [
7]. Randomized prospective case control studies have revealed that nutritional intervention in order to support sufficient energy intake significantly improves patient survival [
8‐
10]. Unfortunately, it is common for cirrhotic patients to present with comorbidities such as hypermetabolism, inefficient digestion and anorexia [
11], which counteract the beneficial effects of sufficient energy intake. The occurrence of hepatic encephalopathy due to an improper protein diet makes it even more difficult to practically maintain nutritional-energy balance during cirrhosis.
Along with energy intake, the body aims to maintain energy balance adopting various ways. In patients with anorexia nervosa, the physiological adaptation to malnutrition is expressed as the refeeding syndrome, when the extra energy is administered even with an appropriate amount to body size [
12,
13]. A daily consumption of a high-fat diet alters the homeostatic regulation [
14‐
16]. Lean people consuming a high-fat diet are associated with increased energy expenditure at rest and a relatively higher fat oxidation to avoid weight gain [
17]. These facts suggest that a nutritional intervention should be adjusted not statically but dynamically in association with personal daily life. In this report, we evaluated dietary intake both at home and in hospital among patients with HCC from the points of PEM, minimal hepatic encephalopathy (MHE) and recovery from cancer treatment, and show that dietary deviation is an important consideration when invasive treatments are planned. In addition, the impact of nutritional intervention is discussed for the optimal management of HCC.
Methods
Patients
Thirty-five consecutive cases suffering from HCC with various histories of liver disease were enrolled in this study (Table
1, Group 1). When hospital admission was primarily to treat HCC, a digital camera and questionnaires were provided to record the diet at home several days before admission. A computer-aided neuropsychiatric test (NP test) and assessment of body composition based on a bioelectrical impedance analysis using InBody system (BIOSPACE, Tokyo, Japan) were performed upon admission. In addition, a dietician calculated energy intake based on Japanese dietary allowance according to home photo images, which were obtained at least three consecutive days prior to the admission both before and after each meal including snacks, and descriptions from the questionnaires. In patients without any special comorbidity such as diabetes mellitus, a regular hospital diet of 1800 kcal/day was served. Any nutritional support including branched-chain amino acids (BCAA) was kept as it was in the outpatient clinic. On the next day, day 1, nitrogen balance and non-protein respiratory quotient (npRQ) were evaluated. On day 4 after admission, one day before the application of invasive therapy, the NP test, nitrogen balance and npRQ were assessed again. The questionnaires and recording of digital photos before and after each meal were continued until day 4 in order to calculate actual energy intake for the hospital and non-hospital provided diet. This study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving human subjects/patients were approved by the Niigata University Graduate School of Medical and Dental Sciences Human Research Committee. Written informed consent was obtained from all patients for publication of individual clinical details.
Table 1
Summary of patients’ characteristics
Age | 68.5 ± 8.2 | 71.0 ± 8.2 |
Gender (male/female) | 28/7 | 14/6 |
Body mass index | 24.3 ± 3.2 | 24.6 ± 3.5 |
Background (HBV/HCV/Alcohol/NASH/PBC/AIH) | 12/14/6/3/1/0 | 4/11/3/1/0/1 |
Child-Pugh score (5/6/7/8/9) | 20/7/6/0/2 | 11/5/3/0/1 |
TNM stage (I/II/III/IV) | 18/9/3/5 | 6/5/4/5 |
Treatment (RFA/TACE/TOCE/HAIC/Sorafenib/No) | 8/6/3/11/1/6 | 4/6/3/7/0/0 |
BCAA supplementation (+/−) | 21/14 | 11/9 |
PT-INR on admission | 1.12 ± 0.09 | 1.09 ± 0.08 |
Neuropsychiatric test
When a patient received an abnormal value for the revised version of the Hasegawa dementia scale [
18], he/she was excluded from this study. MHE was evaluated using a computer-aided quantitative NP test [
19], which consisted of the eight following categorical tests: number connection tests A and B, a figure position test, a digit symbol test, a block design test, and reaction time tests A, B and C. Because the test results were affected by age, abnormality in each category was originally defined as values beyond the 90th percentile for an age-matched value over a 5-year interval, which was obtained from 542 healthy Japanese volunteers from 40 to 69-years old. Unfortunately, there were many patients who were 70-years old or older. To make an assessment for a patient over 69-years old, a linear regression curve was deduced that excluded reaction time tests, which were fit by second-order polynomial non-linear regression. Each regression analysis showed a significant correlation giving r squares of 0.95, 0.93, 0.77, 0.99, 0.91, 0.94, 0.93 and 0.82, respectively. Thus, in this study, value for each test was decided to be abnormal when it exceeded the 90th percentile, which was calculated from the regression curve for the same age. Because many elderly patients do not react properly to the test due to a lack of experience using a computer, MHE was not diagnosed if the abnormal value appeared in one category but normal during the second evaluation. Instead, MHE was diagnosed when an abnormal value was reproducibly recorded even in one category or when abnormal values were obtained at least once in multiple categories.
Measurements of non-protein respiratory quotient and estimations of energy metabolism
Energy metabolism was analyzed using an indirect calorimeter, AERO MONITOR AE300S (Minato Medical Science Co., Ltd. Osaka, Japan), on day 1 and day 4 after overnight bed rest and fasting. Every five seconds, oxygen consumption (VO2) and carbon dioxide production (VCO2) were measured until steady-state values were obtained over two consecutive minutes. A steady state was defined by a variation between 5% and 10% in the average value for oxygen consumption and carbon dioxide production over 3 minutes. npRQ was calculated as an average of the following ratio: VCO2/VO2. Urine urea nitrogen (UUN) was measured by urease indophenol method in urine that was collected throughout the day without any intravenous infusion. Resting energy expenditure (REE) was calculated according to the following formula [
20]: ((15.913 × VO2 + 5.207 × VCO2) × 1.44 - 4.646 × TUN) × 0.239. TUN (total urea nitrogen) was calculated in the urine, which was collected over 24 hours, as UUN + 4 if UUN exceeded 15 g/day; otherwise, TUN was calculated as UUN × 1.17 + 0.7. Basal energy expenditure (BEE) was estimated using a Harris-Benedict equation, in which BEE was 66.5 + (13.75 × body weight in kg) + (5.003 × body height in cm) - (6.775 × age) for males and was 655.1 + (9.563 × body weight in kg) + (1.850 × body height in cm) - (4.676 × age) for females. The daily energy requirement was estimated from REE or BEE by multiplying by stress and activity coefficients of 1.1 and 1.3, respectively. The stress coefficient was selected between no stress; 1.0 and suffering from advanced cancer; 1.2, while the activity coefficient was decided between simple walking; 1.2 and light labour; 1.4, respectively. The protein and energy malnutrition was diagnosed in the case that npRQ was less than 0.85 [
21] as well as nitrogen balance was negative.
Normalization of therapeutic invasiveness using prothrombin time
In order to standardize a recovery speed form HCC treatments based on therapeutic intensity, a reduction rate of prothrombin time (PT-INR) was used as an indicator for the intensity. Given nadir as a day showing minimum value of PT-INR after finishing an entire series of treatment against HCC in one admission, a reduction rate of PT-INR was defined as a reduction percentage of PT-INR at nadir against PT-INR on admission. The formula calculating PT-INR reduction rate is as follows where PT-INRad and PT-INRnad indicate PT-INR on admission and at the nadir after a series of treatment, respectively.
PT-INR reduction rate (%) = (PT-INRad – PT-INRnad)/PT-INRad × 100
Then, a recovery speed from treatments for HCC was evaluated based on a length of hospital satay (day) after nadir that was normalized by dividing with the PT-INR reduction rate as follows.
Recovery speed = hospital stay after PT-INRnad/PT-INR reduction rate × 100
Statistical analysis
Categorical data were compared between two groups using paired or unpaired t tests when groups were matched or unmatched, respectively. Correlation between npRQ and various factors were analyzed by calculating the Pearson correlation coefficient. All analyses were performed using GraphPad Prism 6 software (GraphPad Software, Inc. La Jolla, USA) except for a multivariate linear regression analysis, for which PASW statics 17.0 (SPSS Inc., Chicago, USA) was used, and a two-sided P-value less than 0.05 was considered statistically significant.
Discussion
Several lines of evidence strongly indicate that a functional hepatic reserve possesses similar impacts on the survival of HCC cases with anatomical cancer extension [
3,
4,
22‐
24]. On the other hand, several randomized prospective case control studies have revealed that active nutritional intervention significantly improves the prognosis in patients with liver cirrhosis [
8‐
10]. Taken together with the evidence that energy intake lower than 30 kcal/kg leads to a poor prognosis in cirrhotic patients [
7], it is reasonable to assume that a strategy to preserve functional hepatic reserves should be incorporated into a treatment scheme for HCC. In this report, we first evaluated protein-energy status in patients who were facing active interventional treatments for HCC. In these cases, PEM was clearly present on admission as a negative nitrogen balance and an npRQ less than 0.85 in association with MHE that was diagnosed in 5 out of 35 cases. These results strongly suggest that nutritional intervention should be started before hospitalization in patients with HCC. In terms of nutritional support, BCAA supplementation was reported to elongate event-free survival by improving PEM in cirrhotic patients [
25], while its efficacy was equivocal in cases receiving radiofrequency ablation as the form of HCC treatment [
26]. Although the nitrogen balance and npRQ were not significantly different between cases with and without BCAA supplementation in this study, the limited number of cases does not provide a conclusive result. The significance of BCAA supplementation under active treatments of HCC should be further evaluated in a larger cohort.
It was reported that BEE underestimates energy requirements in patients with liver cirrhosis, which leads to a hypermetabolic state [
27]. Consistently, the BEE-based energy requirement calculated from the Harris-Benedict equation was different from the REE-based estimation more than 10% in more than 44% cases in this study. On the other hand, the total energy intake at home was not significantly different from the daily energy requirement, which was estimated from REE by multiplying 1.1 and 1.3 as the stress and activity coefficients, respectively. Although energy equivalents are considered in the REE-based calculation, these PEM suffering patients suggest that liver cirrhosis affected energy state not only by inducing hypermetabolism but also by hampering the absorption and/or efficient usage of nutrients. Furthermore, the increase of npRQ above 0.85 after admission even with consumption of less energy suggests that it is practically difficult to select appropriate activity and stress coefficients. Taken together, it is strongly recommended that the protein-energy state should be used to define an appropriate daily energy intake in cirrhotic patients using indicators such as npRQ.
The computer-aided NP test is one of the few quantitative approaches for the diagnosis of MHE that were recommended in the guidelines provided by the World Congress of Gastroenterology-commissioned Working Party [
28] due to their high specificity for diagnosing hepatic encephalopathy [
29]. Currently, however, the diagnosis and clinical significance of MHE have not been well defined [
30]. While abnormal values at least in two tests among eight subsets were reported to be required achieving 80% of sensitivity [
31], the same setting were also employed for diagnostic criteria in NP test consisting of four subsets instead of eight [
32]. Another problem for NP test is age dependency [
19]. There are no available control data for patients over the age of 69. Hence, it may be difficult to distinguish an early stage of dementia from MHE. In addition, there is a concern that these results may be affected by unfamiliarity with using a computer device, especially when elderly patients are the subjects. In this study, the 90th percentile for normal controls was estimated in each test from a regression line deduced from the values of controls between ages 40 to 69. A high Pearson’s coefficient value for this regression line demonstrated the goodness of fit for all eight categories. Patients who were diagnosed with dementia were excluded from the study on the basis of a revised Hasegawa dementia scale [
18]. Although senile decay in reaction time and/or cognition may not be completely excluded from our MHE diagnostic criteria, the lower values of npRQ in all 5 MHE-positive patients strongly suggested that MHE diagnosed by our criteria was associated with functional hepatic reserve. Easy and reliable diagnostic criteria for MHE should be further explored through extensive studies using a larger cohort to prove the clinical significance of MHE in association with the energy malnutrition.
This study suggested that an insufficient fat source impaired the recovery from invasive treatments for HCC in cirrhotic patients. An indicator of energy state, npRQ, was significantly changed after admission in association with the energy difference for fat consumed between home and the hospital. Consistent with the association between MHE cases and lower npRQ, the relative energy from fat was significantly lower in the cases that were diagnosed with MHE. Taken together, it is suggested that energy state should be improved before invasive treatments to promote a rapid recovery, and specifically, energy from fat should be provided at a dose recommended for the regular dietary allowance, which is between 20% to 30% of total energy intake [
33,
34]. In terms of normalization of therapeutic invasiveness, PT-INR was employed in this study. Although serum concentrations of NH
3 and total bilirubin were tested for this purpose, these values were prerequisitely altered due to extrahepatic circumstances such as constipation or constitutive jaundice. Because a single criterion of PT-INR was employed, the relationship between fat intake and recovery from HCC treatments should be confirmed using other measures in the future.
Although the limited case numbers in this study may have resulted in an inadequate assessment of the biological variability, as neither npRQ nor MHE was associated with body compositions such as BMI, extra cellular water, percent body fat, soft lean mass, or skeletal muscle amount, it is assumed that orally taken fat was directly consumed as an energy source. Nonesterified fatty acid (NEFA) suppresses gluconeogenesis in the liver through insulin secretion. At the same time, however, NEFA desensitizes the liver to insulin
via insulin receptor substrates, which surpass insulin induction and lead to net elevation of gluconeogenesis [
35‐
40]. Furthermore, fat from diet is absorbed in the form of chylomicrons and is taken up by hepatocytes as a remnant after digestion at the capillary endothelium by lipoprotein lipase [
41], promoting gluconeogenesis as a source of energy and substrates such as acetyl-CoA, NADH and ATP. Through β-oxidation processes, acetyl-CoA is subjected to not only gluconeogenesis but also the generation of ketone bodies, which are major energy sources in the brain [
42]. In a whole body, npRQ could increase as long as peripheral tissues have glucose and/or ketones to oxidize even under the situation where npRQ decreased in the liver due to gluconeogenesis and ketogenesis [
43]. Under PEM, it is teleological for the liver that NEFA uptake is increased in association with up-regulation of gluconeogenesis and ketogenesis [
44]. Recently, it was reported that p38 mitogen-activated protein kinase plays a crucial role in the activation of gluconeogenic genes by NEFA [
45]. Although the results presented here should be confirmed by a large scale study, our notion is in line with the guideline from the European Society for Clinical Nutrition and Metabolism, which recommends 40% to 50% of non-protein energy requirements (more than 30% of total energy requirements) should be provided by lipid in parenteral nutrition in patients with liver diseases [
46]. An appropriate amount of fat intake may have the potential to improve PEM and MHE under the condition such as cirrhosis, in which sugar and protein metabolisms cannot work properly [
47,
48].
Competing interests
All authors declare that they have no competing interest to disclose.
Authors’ contributions
TS designed the research, analyzed data and wrote the manuscript. TK, TK, KY, YSK performed npRQ, MHE, body composition and dietary intake analyses. HN and TM evaluated the results of npRQ and nutritional aspect, respectively, and made disciplinary advice. YA made critical revision of the manuscript for important intellectual content. All authors read and approved the final manuscript.