Background:Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death. Many treatments have been proposed but considerable uncertainty still remains about their effectiveness. In this review we evaluated the quality, clinical coherence, consistency and results of Randomized Controlled Trials (RCT) of non-surgical treatments for HCC.Methods:Thirty-seven RCTs examining the effect of different treatments were retrieved using MEDLINE (November 1978 to December 1995) and a review of reference lists. Selected aspects of the quality of design, conduct and reporting were examined. The odds ratio for the probability of surviving up to one year was calculated according to the Mantel-Haenszel-Peto method and displayed using l'Abbé plots.Results:The 37 RCTs overall included 2803 patients (median 56, range 20-289). Patients prognosis varied widely across studies which also failed to report on important information about their characteristics. Only 10 RCTs had an untreated control group; the remaining 27 compared different regimens of intravenous or intraarterial chemotherapy with or without embolization of hepatic artery, hormono- and immunotherapy regimens. Some evidence of a moderate benefit emerged only from RCTs using tamoxifen and transcatheter arterial embolization vs. no treatment in unresectable patients: pooled odds ratio for 1-year survival were, respectively, 2.0 (95% confidence intervals (CI) 1.1–3.6) and 2.0 (95% CI 1.1–3.6). At 2 years, however, pooled odds ratio were no longer statistically signscant for tamoxifen 1.2 (95% CI 0.6–2.6) but was significant for embolization 2.3 (95% CI 1.2–4.6). No evidence of efficacy was detected for embolization as adjuvant therapy in resected or transplantated patients nor for chemotherapy added to intraarterial embolization.Conclusions:This systematic review of RCTs on HCC, mostly in non resectable patients, indicate that the non-surgical current treatments are ineffective or minimally and uncertainly effective. The three treatment modalities minimally and uncertainly effective (i.e., embolization, tamoxifen and IFN) can deserve further assessment by larger and methodologically more sound randomized trials.

PURPOSE: To investigate whether paclitaxel and docetaxel influence the pharmacokinetics and metabolism of epirubicin. PATIENTS AND METHODS: We studied the pharmacokinetics and biotransformation patterns of epirubicin in 27 cycles and 20 breast cancer patients. Four patients received epirubicin alone 90 mg/m² by intravenous (IV) bolus; eight patients received the same dose of epirubicin followed immediately by paclitaxel 175 mg/m² in a 3-hour infusion; the other eight patients received epirubicin 90 mg/m² followed immediately by docetaxel 70 mg/m² in a 1-hour infusion. Epirubicin and its metabolites, epirubicinol (EOL) and 7-deoxydoxorubicinone (7d-Aone), were identified by high-pressure liquid chromatography. RESULTS: No pharmacokinetic interaction between the parent compound epirubicin and taxanes was detected. Conversely, a significant effect on epirubicin metabolism by both paclitaxel and docetaxel was found. Epirubicin given with paclitaxel or docetaxel yielded areas under the plasma concentration-time curves (AUC) for 7d-Aone 1.7-fold and 1.9-fold higher (P < .05), respectively, than epirubicin alone. The appearance of two polar metabolites sensitive to glucuronidase was also significantly greater in both taxane groups. Quantitatively different metabolic rates and patterns for EOL were observed in the paclitaxel and docetaxel combinations. The EOL AUC after paclitaxel treatment (1,521 ± 150 ng/mL*h) was significantly higher (P < .01) than the corresponding values after epirubicin administered either as a single agent (692 ± 46 ng/mL*h) or in combination with docetaxel (848 ± 237 ng/mL*h). CONCLUSION: There is no apparent pharmacokinetic interaction between the parent compound epirubicin and paclitaxel or docetaxel. A different pattern of interaction between these taxanes and epirubicin metabolism is clearly evident.

PURPOSE: Sequence-dependent clinical and pharmacokinetic interactions between paclitaxel and doxorubicin have been reported. Some data have shown an influence of paclitaxel on epirubicin metabolism, but no data are available about the effect of diverse sequences of these drugs. We investigated whether reversing the sequence of epirubicin and paclitaxel affects the pattern or degree of toxicity and pharmacokinetics.PATIENTS AND METHODS: Patients receiving epirubicin 90 mg/m²by intravenous bolus followed by paclitaxel 175 mg/m²over 3-hour infusion or the opposite sequence every 3 weeks for four cycles were eligible. Toxicity was recorded at nadir. Pharmacokinetic data were evaluated at the first and the second cycle and were correlated with toxicity parameters.RESULTS: Thirty-nine consecutive stage II breast cancer patients were treated. Twenty-one patients received epirubicin followed by paclitaxel (ET group), and 18 received the opposite sequence (TE group). No significant difference in nonhematologic toxicity was seen. A lower neutrophil and platelet nadir and a statistically significant slower neutrophil recovery was observed in the TE group. Area under the concentration-time curve (AUC) of epirubicin was higher in the TE group (2,346 ng/mL · h v 1,717 ng/mL · h; P = .002). An inverse linear correlation between epirubicin AUC and neutrophil recovery was also observed (P = .012). No difference was detected in paclitaxel pharmacokinetics.CONCLUSION: Our results support a sequence-dependent effect of paclitaxel over epirubicin pharmacokinetics that is associated with increased myelotoxicity. Because schedule modifications of anthracyclines and paclitaxel can have clinical consequences, the classical way of administration (ie, anthracyclines followed by paclitaxel) should be maintained in clinical practice.

To evaluate the quality of patients care, a set of indicators of the standards of cancer care were defined. We developed a set of indicators to assess the implementation in daily practice of recommendation produced by a regional network (Istituto Toscano Tumori). This set was tested in a retrospective study in the resident population of the Tuscany Region; the regional health system is organized on 12 local health authorities which refer to three macro areas (Area Vasta). The study included incident colorectal, lung and breast cancer cases listed in 2004 for the Tuscan Cancer Registry, a population-based registry which collected tumor cases diagnosed in all residents in Tuscany. Electronic data from registry database were used to determine the compliance with each indicator for patients in 2004. To validate the results, an ad hoc clinical survey including the same geographical area for the year 2006 was performed. None. The proportion of patients who fulfilled each of the indicators. Our study showed the feasibility of the evaluation of the quality of cancer care using cancer registry population-based data and major computerized information systems. The estimation of the selected indicators confirmed a good homogeneity among areas, and globally revealed a good intraregional performance. Further work is needed to develop specific quality measures, particularly about structural data and to continually revise indicators of quality of care. Data from a cancer registry, however, can be useful to evaluate quality of cancer care

This monograph highlights the multiple payoffs from comparing patterns of cancer care, costs, and outcomes across health systems, both within a single country or across countries, and at a point in time or over time. The focus of comparative studies can be on the relative performance of systems in delivering quality cancer care, in controlling the cost of cancer care, or in improving outcomes, such as reducing mortality rates and improving survival. The focus also can be on comparing the effectiveness, cost, or cost-effectiveness of competing cancer prevention and control interventions within a given system or across systems, while taking into account variations in patient characteristics, disease incidence and severity, resource availability, unit costs, and other factors influencing system performance.