As mentioned in the introduction section, peg-IFN α plus RBV combination will be in demand for the foreseeable future. Patients at a high risk of developing RBV-induced hemolysis will expose themselves to a more increased risk for treatment-induced anemia in triple combination treatment. Identifying such high-risk patients and predicting the severity of anemia in individuals may provide an early decision to commence treatment with normal or reduced dosage and to keep the dose reduction to a minimum to lessen the disadvantages of anemia with adequate exposure to RBV continuing. To date, many studies have proposed factors that could influence the probability of clinically significant anemia in RBV-based treatment: age, sex[11,12
], race, pre-existing cirrhosis[14
], baseline Hb concentration[11,20
], drug exposure[12-14
], plasma RBV concentration[10
], Hb decline at week 2 of treatment[12,14,20
], and SNPs at the ITPA
] and nucleoside transporter genes[19
]. However, the definition of anemia or end point of analysis varied a little among previous studies, possibly leading to alteration of significant predictors. Despite these useful predictors, there is no convenient prediction model or formula for estimating the likelihood of clinically significant anemia that has been defined previously and used generally[15
]. This study provided relevant numerical expressions constructed by independent variables for predicting the differentially defined anemia: Hb concentration < 10.0 g/dL (significant anemia) and a decline in Hb concentration > 3.0 g/dL (significant Hb decline) at week 4 of treatment and qualitative Hb decline at week 2 and 4. This is believed to be the first report to construct the prediction models by using reliable factors: the ITPA
SNP rs1127354, baseline Hb concentration, estimated GFR, and quantitative Hb decline at week 2 of treatment, irrespective of the different definitions of anemia. The significant baseline factors that were shown in this study appear to influence treatment-induced anemia in triple combination treatment (under investigation, data not shown).
Two functional ITPA
variants conferring ITPA deficiency or reduced activity are known to contribute most to protection against RBV-induced hemolytic anemia[15-18
]. Inosine triphosphate (ITP) is hydrolyzed by ITPA to inosine monophosphate. Therefore, ITPA deficiency or low activity causes the accumulation of ITP in red blood cells (RBCs)[24-26
]. The accumulated ITP may compete with the accumulated triphosphate form of RBV that could mediate oxidative damage to the RBC membrane and extravascular destruction[25-27
], thereby protecting RBCs against RBV-induced hemolysis. As also shown in this study, one functional SNP rs1127354 is prominently associated with differentially defined anemia. Of note, however, the SNP was not always a factor of the top significance. The combined ITPA activity variable with another functional SNP rs7270101 is a stronger determinant of anemia than either ITPA
SNP alone in European-Americans[16
], whereas rs7270101 is not polymorphous in the Japanese population as registered in the HapMap database and reported by others[17,18,23
]. One SNP, rs6051702 at the C20orf194
located near the ITPA
, linked to the ITPA
SNPs, also confers protection against anemia in European-Americans[15
], while the association was statistically significant but weak in one Japanese cohort[18
]. This Japanese study population showed no significant association (Table ), supporting that rs1127354 is a single causal variant responsible for protection against anemia in the Japanese genetic cohort[17
Certainly, the ITPA
SNP rs1127354 minor variant A is a strong protective allele for anemia. In this overall cohort, none (0%) and three (3%; who had genotype CA) of patients with minor variant A had significant anemia and significant Hb decline, respectively (Figure ). Therefore, negative predictive value of minor variant A was 100% and 97.7%, respectively. The noticeable distinction was in excellent agreement with other studies[15,18
]. With respect to the likelihood of these anemic events, patients with minor variant A may be monitored less intensively and recommended to receive normal RBV doses, even in patients with relatively low baseline Hb, or more aggressive dose escalation strategies irrespective of baseline Hb. It is noteworthy that genotype AA patients with predicted ITPA deficiency, including seven patients with baseline Hb < 13.0 g/dL (range, 11.7-12.9 g/dL), showed no or little change in the Hb concentration (data not shown), although the number was small.
As shown in this study and another[18
], however, only 25% of the Japanese population has minor variant A. The remaining 75% have major genotype CC. Positive predictive values of major genotype CC alone for significant anemia and significant Hb decline were low (14.3% and 39.1%, respectively), and values of predictive accuracy were low (35.7% and 53.5%, respectively). The range of Hb decline varied widely among individuals with genotype CC, indicating that some of them showed little or no change in Hb decline. Even in minor genotype CA carriers, it also varied widely and was similar to that of genotype CC patients (Figure ). These findings strongly suggest that any factors other than the strong predictor ITPA
SNP could affect hemolysis positively or negatively. Therefore, it is highly unlikely that the ITPA
SNP (except genotype AA) is used alone to determine clinical decision making for treatment modification. In fact, several factors independently and strongly influenced treatment-induced anemia as well as the ITPA
SNP in this study.
The clearance rate of RBV from the body is of critical importance for influencing treatment outcome and RBV-induced anemia, because the clearance parameters, such as CL/F and Ccr, reflect plasma/serum RBV concentrations at week 4 of treatment, which means the steady phase of treatment[8-10,14,20,28
]. Higher or lower values of the parameters are correlated closely with lower or higher plasma/serum concentrations, respectively. Higher plasma/serum concentrations lead to an increased risk for progression of anemia as well as the higher probability of achieving SVR. Indeed, this study confirmed that the clearance rate is associated significantly and independently with RBV-induced anemia irrespective of the different definitions. This study also analyzed which of three parameters estimated by the formulae were the most stable for predicting clinically significant anemia. These formulae are composed by age, sex, BW and serum creatinine. Age and sex have been reported to affect treatment-induced anemia and dose reduction, and could reflect reactivity to treatment, tolerance and pharmacological metabolism[11,12,29
]. Japan is one of the countries with the longest living people and the world’s fastest aging society, therefore, the clearance rate should especially be taken into account in RBV-based treatment of Japanese patients. The reason that estimated GFR remained an independent factor in the final model may be that the formula has been built up based on data from the Japanese population.
Higher baseline Hb concentration was significantly associated with the likelihood of significant Hb decline. Conversely, lower baseline Hb concentration was linked to significant anemia. These findings may be a matter of course. However, most of this study population received treatment without RBV dose reduction as scheduled, suggesting that kinetics of Hb decline within the first 4 wk of treatment might be delayed in patients with lower baseline Hb concentration. A certain threshold of Hb concentration might limit the progression of anemia independent of baseline Hb concentration. At least in Japanese patients, the two different definitions of anemia, significant Hb decline and significant anemia, should be separately analyzed and discussed.
In this multivariate analysis, qualitative Hb decline at week 2 of treatment was most highly predictive of significant Hb decline, compared to the strong predictor ITPA
SNP rs1127354 and other baseline factors. Previous studies have shown that Hb decline of 2.0 g/dL at week 2 of treatment was predictive of Hb concentration < 10 g/dL or < 8.5 g/dL during the treatment[12,20
]. In another study, Hb decline of 1.5 g/dL at week 2 was predictive of Hb decline ≥ 2.5 g/dL at week 4[14
]. In this ROC analysis, the best cutoff value for Hb decline at week 2 was 1.45 g/dL. Taken together, Hb decline at week 2 is an excellent early predictor of subsequent Hb decline and could identify candidates for early intervention to maintain RBV dosing and adequate exposure. Indeed, the formula including this on-treatment variable improved positive and negative predictive values and predictive accuracy for significant anemia and significant Hb decline. When considered along with other independent baseline factors predictive of qualitative Hb decline at week 4, the final model yielded high significant values that represented goodness of fit. Using such a timely on-treatment variable and formula, more exact identification of patients prone to clinically significant anemia, early intervention with RBV dose reduction, and more careful monitoring may be indicated to reduce anemia-related adverse effects and avoid premature discontinuation of RBV.
ITPA SNP rs1127354, baseline Hb concentration and estimated GFR influenced Hb decline at week 2 significantly and independently, as well as that at week 4. However, it appears to be difficult to predict qualitative Hb decline at week 2 by using the multiple linear regression model. The point for attention is that the models and formulae did not perfectly predict the likelihood of the anemia, strongly suggesting the possibility that other unidentified factors associated with early occurring anemia might be lost, such as rare SNPs, brittleness of the RBC membrane against intracellular triphosphate form of RBV, or intracellular concentration of ITP.
In conclusion, convenient formulae for qualitatively or quantitatively predicting the likelihood of differentially defined anemia could be generated by significant independent factors in RBV-based treatment for chronic HCV infection. Such trial modeling may be useful in guiding clinical decision making on treatment modification: identifying the predisposition to develop RBV-induced anemia before treatment initiation or at the early treatment phase, and developing the individual tailoring and optimization of RBV dosage to maximize the treatment efficacy and minimize RBV-related adverse effects.