- Top of page
Aims To verify whether fluorouracil (FU) clearance (CL) and volume of distribution (Vss) are better correlated with specific body compartments, such as body cell mass (BCM), total body water (TBW) or fat free mass (FFM), rather than with body surface area (BSA) or total body weight (BW).
Methods Thirty-four patients (13 females and 21 males) affected by colorectal cancer and receiving FU as adjuvant therapy entered the study. CL and Vss were determined after a 2 min i.v. injection of FU (425 mg m−2) and leucovorin (20 mg m−2). Body composition, in terms of BCM, TBW and FFM, was evaluated non-invasively by bioelectrical impedance analysis (BIA).
Results Significant but poor correlations were found between CL or Vss and most anthropometric parameters, including BIA-derived measures (r2 range=0.10–0.21). However, when multiple regression analysis was performed with sex, TBW and FFM as independent variables, the correlations improved greatly. The best correlation was obtained between CL and sex (r2=0.44) and between Vss and sex (r2=0.36). FFM-normalized CL was significantly higher in women than in men (0.030±0.008 vs 0.022±0.005 l min−1 kg−1; 95% CI of difference 0.012, 0.003; P=0.003), suggesting that FU metabolism is more rapid in females. Surprisingly, Vss was highly correlated with CL (r2=0.67; CL=0.52+Vss×0.040). This finding may either be explained by extensive drug metabolism in extra-hepatic organs or by variable inactivation on first-pass through the lung. Both these hypotheses need experimental validation.
Conclusions The pharmacokinetics of FU are better predicted by FFM and TBW than by standard anthropometric parameters and predictions are sex-dependent. The use of BIA may lead to improved dosing with FU.
- Top of page
Fluorouracil (FU) is still used to treat a variety of solid tumours and in particular, in combination with leucovorin, is the standard treatment for adjuvant chemotherapy of colorectal cancer . One major hindrance to optimizing treatment with FU is its considerable interpatient pharmacokinetic variability, which leads to unpredictable plasma drug concentrations [2, 3]. In humans, more than 80% of an i.v. dose of FU is eliminated from the body via reductive metabolism by dihydropyrimidine dehydrogenase (DPD) . Plasma drug clearance is highly variable and depends on dose, exhibiting saturation kinetics , time of day  and administration schedule (i.v. bolus or prolonged infusion) . Even when the drug is given under standardized conditions, namely at the same dose, infusion duration, time of day, a large interindividual variability in clearance has been reported . Pharmacokinetic-pharmacodynamic correlation studies have shown that, following continuous 5FU i.v. infusion, clinical response and/or toxicity are related to the area under the plasma concentration vs time curve (AUC)  and that individual FU dose adjustment with pharmacokinetic monitoring provides high response and survival rates associated with good tolerability . Although the usefulness of monitoring FU AUC following i.v. bolus administration has not yet been established, preliminary findings from our laboratory  suggest that a correlation between AUC and FU toxicity does exist.
Factors, such as sex, age and DPD activity in peripheral blood mononuclear cells, have been shown to be correlated with FU clearance, but these relationships are generally weak, such that most variability in clearance remains unexplained . Although FU is a hydrophilic drug (octanol/water partition coefficient=0.1) , it passes across biological membranes easily by saturable active transport , thus reaching its sites of action and elimination. Since FU plasma clearance after prolonged i.v. infusion largely exceeds liver blood flow and even cardiac output, its metabolism must also occur in extra-hepatic tissues .
On the basis of these considerations, FU clearance and volume of distribution are probably related to body composition, particularly body cell mass (BCM), fat free (lean) mass (FFM) and total body water (TBW). BCM, FFM and TBW can be estimated by bioelectrical impedance analysis (BIA), a noninvasive technique which measures the resistance (R) and reactance (Xc) of the body to the flow of a low-voltage alternating current [14, 15].
The aims of our study were to assess whether body composition parameters as assessed by BIA are correlated with FU clearance and volume of distribution, and whether this correlation is strong enough to permit a better prediction of FU pharmacokinetic parameters than that obtained with standard anthropometric measures, namely body weight and body surface area.
- Top of page
Table 1 shows the main demographic and BIA parameters found in males, females, and in the whole study population. Females had significantly lower body weight (BW), body surface area (BSA), TBW and FFM when compared with males. Mean ages and BCM were not significantly different between the two groups. TBW and FFM but not BCM represented a significantly smaller percentage of BW in females than in males (TBW=51.1±4.5% vs 57.7±3.9%, 95% CI on the difference 4.0, 10.8, P<0.0001; FFM=65.2±5.6% vs 74.1±6.8%, 95% CI 4.1, 14.9, P=0.0004; BCM= 30.8±5.8% vs 30.4±5.2%).
Table 1. Patients' characterisitics (mean±s.d.).
| ||Age (years)||BW (kg)||BSA (m2)||R (Ω)||Xc (Ω)||TBW (kg)||FFM (kg)||BCM (kg)|
FU plasma concentration-time curves were better described by a 2 compartment than a 1 compartment linear model in 22 out of 34 patients. In the 12 remaining subjects, a 1 compartment model was more appropriate. In all cases, r2 was>0.96 (mean±s.d.: 0.99±0.01). Table 2 summarizes the mean values for dose, AUC, CL, CL/kg, Vss, Vss/kg, Vc, initial and terminal half-life in males, females, and all patients. None of the pharmacokinetic parameters differed between males and females (apart from the absolute dose, which was lower in females) or was related to age.
Table 2. Pharmacokinetic parameters of FU (mean±s.d.).
| ||Dose (mg)||AUC (mg l−1 min−1)||CL (l min−1)||CL/kg (l min−1 kg−1)||Vss (l)||Vss/kg (l kg−1)||Vc § (l)||Final t½ (min)||Initial t½§ (min)|
Significant but poor correlations were found over the whole population between BW, BSA, TBW, FFM, BCM and CL, and between BW, TBW, FFM and Vss (Table 3). BSA and BMC were not significantly correlated with Vss.
Table 3. Correlations between FU pharmacokinetic and anthropometric parameters in the whole population, as expressed by r2 and P values (brackets).
|(0.013)||(0.071, NS)||(0.018)||(0.014)||(0.052, NS)|
Whereas no significant differences between sexes were found in correlations between BW, BSA and BCM, and CL and V (Figure 1), the regression lines for TBW and FFM had significantly greater Y-intercepts in females than in males, but without differences in slope (Figure 2). Furthermore, coefficients of determination (r2) obtained separately in men and women were substantially higher than those found in the whole population (Tables 3 and 4).
Figure 1. Relationships between BIA measures (BW, BSA and BCM) and FU pharmacokinetic parameters (CL and Vss). Since all regression lines did not significantly differ between sexes, only lines referring to the combined data are shown. ○: females; •: males.
Download figure to PowerPoint
Figure 2. Relationships between BIA measures (TBW and FFM) and FU pharmacokinetic parameters (CL and Vss). Regression lines were significantly different between females (○) and males (•). P values refer to differences in intercepts.
Download figure to PowerPoint
Table 4. Correlations (r2) between FU pharmacokinetic parameters and selected BIA measures (TBW and FFM), in males and females as expressed by r2 and P values.
| || ||TBW||FFM|
According to the stepwise multiple regression analysis performed with TBW and FFM as continuous variables, and sex as a categorical variable (females=0; males=1), FFM and sex were significantly related to CL, whereas TBW and sex were related to Vss. Thus, since FFM and TBW were highly correlated with each other (r2=0.95), they explained much of the variance in CL and Vss. The corresponding regression models were as follows:
- CL=-0.56+FFM (0.044-SEX×0.61; r2=0.44; adjusted r2=0.41; P<0.00011)
- Vss=-15.76+TBW×1.05-SEX×10.50; r2=0.36; adjusted r2=0.32; P<0.0010
A multiple regression analysis including sex as a categorical variable was also performed for BW, given this was the non-BIA parameter best correlated with CL and Vss. The following equations were obtained:
- CL=-0.152+BW×0.022-SEX×0.25; r2=0.29; adjusted r2=0.25; P<0.0044
- Vss=-9.74+BW×0.42-SEX×3.10; r2=0.23; adjusted r2=0.18; P<0.017
It appears that, like with FFM and TBW, the correlation between BW and CL and Vss improves by including sex as an additional variable.
Since FFM and TBW were the parameters best correlated with CL and Vss, respectively, we normalized CL by FFM and Vss to TBW in males and females. Both FFM-normalized CL (CL/FFM) and TBW-normalized Vss (Vss/TBW) were significantly higher in women than in men (CL/FFM: 0.030±0.008 vs 0.022± 0.005 l min−1 kg−1, 95% CI 0.003, 0.012, P=0.003; Vss/TBW: 0.54±0.15 vs 0.41±0.16 l kg−1, 95% CI 0.057, 0.128, P=0.032).
The finding that both CL and Vss correlated with hydrophilic body compartments (FFM and TWW) prompted us to test whether Vss and CL were also correlated with each other. A very good relationship was found between these two parameters in the population as a whole (r2=0.67; CL=0.52+Vss×0.040) but, at variance with the FFM and TBW correlations, no difference emerged between the regression lines of males and females (Figure 3). The relationship was still highly significant when Vss/kg and CL/kg were used instead of Vss and CL (r2=0.55), indicating that body size played a minor role in explaining the correlation between CL and Vss.
Figure 3. Relationship between Vss and CL. ○: females; •: males. Asterisks and crosses: data (not included in regression analysis) taken from references 26 and 27, respectively.
Download figure to PowerPoint
In summary, FFM and TBW are better predictors of CL and Vss, respectively, than BW and BSA when data from males and females are analysed separately, and Vss appears to be the best predictor of FU CL, independent of sex.