ABSTRACT: Sarcomas are rare tumors (1-2% of all cancers) of mesenchymal origin that may develop in soft tissues and viscera. Since the International Classification of Disease (ICD) attributes visceral sarcomas (VS) to the organ of origin, the incidence of sarcoma is grossly underestimated. The rarity of the disease and the variety of histological types (more than 70) or locations account for the difficulty in acquiring sufficient personal experience. In view of the above the European Commission funded the project called Connective Tissues Cancers Network (CONTICANET), to improve the prognosis of sarcoma patients by increasing the level of standardization of diagnostic and therapeutic procedures through a multicentre collaboration.
Two protocols of epidemiological researches are here presented. The first investigation aims to build the population-based incidence of sarcoma in a two-year period, using the new 2002 WHO classification and the "second opinion" given by an expert regional pathologist on the initial diagnosis by a local pathologist. A three to five year survival rate will also be determined. Pathology reports and clinical records will be the sources of information.The second study aims to compare the effects on survival or relapse-free period - allowing for histological subtypes, clinical stage, primary site, age and gender - when the disease was treated or not according to the clinical practice guidelines (CPGs).
Within CONTICANET, each group was asked to design a particular study on a specific objective, the partners of the network being free to accept or not the proposed protocol. The first protocol was accepted by the other researchers, therefore the incidence of sarcoma will be assessed in three European regions, Rhone-Alpes and Aquitaine (France) and Veneto (Italy), where the geographic distribution of sarcoma will be compared after taking into account age and gender. The conformity of the clinical practice with the recommended guidelines will be investigated in a French (Rhone Alps) and Italian (Veneto) region since the CPGs were similar in both areas.
BMC Public Health 04/2010; 10:188. · 2.00 Impact Factor
ABSTRACT: It is debated whether patients with melanoma who undergo lymphadenectomy after a positive sentinel lymph node (SN) biopsy (SNB) have a better prognosis compared with patients who are treated for clinically evident disease.
The records of 190 patients with cutaneous melanoma who underwent radical lymph node dissection after a positive SNB (completion lymph node dissection [CLND]; n = 100) or who had clinically evident lymph node metastasis (therapeutic lymph node dissection [TLND]; n = 90) were analyzed. Moreover, the MEDLINE, EMBASE, and Cochrane databases were searched for studies that investigated the survival impact of SNB-guided CLND compared with TLND for clinically evident disease. Standard meta-analysis methods were used to calculate the overall treatment effect across eligible studies.
In the authors' series, tumor characteristics did not differ significantly between patients who underwent CLND and those who underwent TLND. After a median follow-up of 52.6 months, the 5-year overall survival rate did not differ significantly between CLND patients and TLND patients (68.9% vs 50.4%, respectively; log-rank test; P = .17). In contrast, a meta-analysis of 6 studies (n = 2633) that addressed this issue (including the authors' own series) indicated that there was a significantly higher risk of death for patients who underwent TLND compared with that for patients who underwent CLND (hazard ratio, 1.60; 95% confidence interval, 1.28-2.00; P < .0001).
Although no significant survival difference was observed in either series, the pooling of summary data from all the studies that dealt with this issue suggested that SNB-guided CLND is associated with a significantly better outcome compared with TLND for clinically evident lymph node disease.
Cancer 03/2010; 116(5):1201-9. · 4.77 Impact Factor
ABSTRACT: To improve selection for sentinel node (SN) biopsy (SNB) in patients with cutaneous melanoma using statistical models predicting SN status.
About 80% of patients currently undergoing SNB are node negative. In the absence of conclusive evidence of a SNBassociated survival benefit, these patients may be over-treated. Here, we tested the efficiency of 4 different models in predicting SN status.
The clinicopathologic data (age, gender, tumor thickness, Clark level, regression, ulceration, histologic subtype, and mitotic index) of 1132 melanoma patients who had undergone SNB at institutions in Italy and Australia were analyzed. Logistic regression, classification tree, random forest, and support vector machine models were fitted to the data. The predictive models were built with the aim of maximizing the negative predictive value (NPV) and reducing the rate of SNB procedures though minimizing the error rate.
After cross-validation logistic regression, classification tree, random forest, and support vector machine predictive models obtained clinically relevant NPV (93.6%, 94.0%, 97.1%, and 93.0%, respectively), SNB reduction (27.5%, 29.8%, 18.2%, and 30.1%, respectively), and error rates (1.8%, 1.8%, 0.5%, and 2.1%, respectively).
Using commonly available clinicopathologic variables, predictive models can preoperatively identify a proportion of patients ( approximately 25%) who might be spared SNB, with an acceptable (1%-2%) error. If validated in large prospective series, these models might be implemented in the clinical setting for improved patient selection, which ultimately would lead to better quality of life for patients and optimization of resource allocation for the health care system.
Annals of surgery 12/2009; 250(6):964-9. · 7.90 Impact Factor
ABSTRACT: Current clinical and histopathological criteria used to define the prognosis of melanoma patients are inadequate for accurate prediction of clinical outcome. We investigated whether genome screening by means of high-throughput gene microarray might provide clinically useful information on patient survival.
Forty-three tumor tissues from 38 patients with stage III and stage IV melanoma were profiled with a 17,500 element cDNA microarray. Expression data were analyzed using significance analysis of microarrays (SAM) to identify genes associated with patient survival, and supervised principal components (SPC) to determine survival prediction.
SAM analysis revealed a set of 80 probes, corresponding to 70 genes, associated with survival, i.e. 45 probes characterizing longer and 35 shorter survival times, respectively. These transcripts were included in a survival prediction model designed using SPC and cross-validation which allowed identifying 30 predicting probes out of the 80 associated with survival.
The longer-survival group of genes included those expressed in immune cells, both innate and acquired, confirming the interplay between immunological mechanisms and the natural history of melanoma. Genes linked to immune cells were totally lacking in the poor-survival group, which was instead associated with a number of genes related to highly proliferative and invasive tumor cells.
Journal of Translational Medicine 02/2006; 4:50. · 3.41 Impact Factor