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Introduction: Capecitabine is an oral fluropyrimidine carbamate, converted to 5-Fluorouracil (5FU) predominantly in tumour tissue, prescribed in the treatment of colorectal and breast cancer. Compared to intravenous fluorouracil plus leucovorin, capecitabine shows an at-least equivalent efficacy in terms of time to disease progression and survival and a better tolerability (1,4). In these studies, the Hand-and-Foot Syndrome (HFS) is the only toxicity more frequent with capecitabine than with 5FU, and in fact is the most frequent toxicity of this treatment. It is characterized by cutaneous toxicity, pain, redness, scaling and shedding of the skin of palms and soles and measured by a score representing its severity, scaling from 0 (none) to 3 (skin changes with pain, interfering with function). For therapeutic drug adjustment or testing different dosage regimen, it would be valuable to have a model predicting those scores given drug exposure; but most of the times drug exposure cannot be derived since those studies do not include PK data. However it is possible, using a KPD like approach (2), to derive such a model in certain circumstances were series of scores are collected on long interval times and number of patients is large.

Objectives: To model the longitudinal toxicity score experienced by patients affected with a colorectal cancer, and treated by an oral cytotoxic agent, capecitabine. This model for ordered categorical data includes the effect of the quantity of drug accumulated throughout the treatment without any pharmacokinetic information, and the score experienced at previous time.

Patients & Data: 1207 patients were randomised in two large phase III studies (1,4), which compared the efficacy and the toxicity of 5FU administered intravenously versus oral capecitabine, as first line treatment of metastatic colorectal cancer. Patients were treated over 32 weeks or until disease progression; in responding patients, treatment duration was up to 48 weeks. The median duration of capecitabine treatment was 146 days. Given treatment interruptions at the end of treatment period for many patients, only the first 30 weeks of treatment were modelized. Since very few occurrences of grade 3 were observed, grades 2 and 3 were grouped to a single category. Therefore 3 different scores (0, 1, and ≥2) were considered into the model. Covariates such as age, sex, height, weight, body surface area and type of cancer were considered. Among the 595 patients in capecitabine arm we randomly selected 400 patients to build the model (“building” data set) while 195 were assigned for model qualification (“qualification” data set).

Methods: The probability of experiencing a score of HFS was modelled with an extension of proportional odds ratio model as proposed by Lewis Sheiner (3). The extensions concerned the use of a KPD model for drug exposure and conditional probabilities (Markov model) on transitions from one score to another. Since no pharmacokinetic information was available in those patients, a drug accumulation in the body and a mono-exponential elimination were assumed, which is the principle of the KPD model (2). The parameters of the model were estimated by the Laplacian method implemented in NONMEM software. In the model building process, predictive checks guided the choice of best model as follows: confidence intervals of time-dependant predicted probabilities were compared to observed probabilities. Predicted probabilities were computed by simulating the HFS scores in 100 new building datasets using a degenerate posterior distribution (5).
Once the final model was established, it was qualified by predictive check. We simulated 500 times the toxicity profiles from qualification data set, using the model and likelihood estimates obtained from the building data set. Comparisons were performed between the distribution of number of transitions from one grade to another computed in each simulated data set, and the observed one in the qualification data set.

Results:
Model specification: The final model was a longitudinal proportional odds ratio model with KPD and Markovian component, ie the probability of experiencing a HFS grade was related to the amount of capecitabine administered and to the HFS grade experienced the week before. Tests for covariates effect were performed, and only AGE was significant. Final model is:

Logit{P(Y = 0)}  =  B0 -

EMAX * (Q*K) (Q*K) + ED50

+ θAGE*(AGE-64) + ηi

Logit{P(Y ≤ 1)}  =  B0 + B1 -

EMAX * (Q*K) (Q*K) + ED50

+ θAGE*(AGE-64) + ηi

P(Y = 2)  =  1 - P(Y ≤ 1)

where

• Q is the accumulated dose with an elimination rate constant K (mono-exponential elimination);
• B₀ and B₁ > 0 are the logit intercepts for ordered model;
• E_MAX and ED₅₀ are the maximum effect and apparent dose producing 50% decrease of Emax;
• (AGE-64) is the difference of the AGE with the population median age;
• η_i, η_K are inter-individual variabilities on logit and K.
• the parameters B₀, B₁ and E_MAX are dependent of the score at the previous time, which introduces the Markov assumption.