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El término «precanceroso» debería dejar de utilizarse y sustituirlo por el de «potencialmente maligno», que refleja mejor una evolución nada sistemática. Entre las afecciones potencialmente malignas, la leucoplasia es la más frecuente y la eritroplasia es bastante rara. Siempre se definen por exclusión de lesiones blancas o eritematosas de origen conocido. A pesar de los numerosos avances de la biología molecular, actualmente no existe ningún marcador que permita predecir la transformación maligna en la práctica. Cuando es posible, el tratamiento principal de estas lesiones es quirúrgico, haya o no displasia, que es un concepto puramente histológico. No se sabe si esto realmente previene la aparición del carcinoma epidermoide, el principal cáncer de la mucosa oral. La transformación maligna del liquen plano oral, que es muy inferior que la de la leucoplasia, es más conocida. Actualmente no existe ningún tratamiento que pueda prevenirla. Otras afecciones potencialmente malignas, la fibrosis submucosa, la queilitis actínica, el lupus y las inmunodeficiencias son mucho más raras.

Objective To assess whether differences in safety profiles between nevirapine (NVP) and efavirenz (EFV), as observed in the 2NN study, translated into differences in ‘health related quality of life’ (HRQoL).Design A sub-study of the 2NN study, with antiretro-viral-naive patients randomly allocated to NVP (once or twice daily), EFV or NVP+EFV, in addition to stavudine and lamivudine.Methods Comparing differences in changes of HRQoL over 48 weeks as measured with the Medical Outcomes Study HIV Health Survey (MOS-HIV) questionnaire, using analysis of variance.Results The 2NN study enrolled 1216 patients. No validated questionnaires were available for 244 patients, and 55 patients had no HRQoL data at all, leaving 917 patients eligible for this sub-study. A total of 471 (51%) had HRQoL measurements both at baseline and week 48. The majority (69%) of patients without HRQoL measurements did, however, complete the study. The change in the physical health score (PHS) was 3.9 for NVP, 3.4 for EFV and 2.4 for NVP+EFV (P=0.712). For the mental health score (MHS) these values were 6.1, 7.0 and 3.9, respectively (P=0.098). A baseline plasma HIV-1 RNA concentration (pVL) =100 000 copies/ml and a decline in pVL (per log10) were independently associated with an increase of PHS. An increase of MHS was only associated with pVL decline. Patients experiencing an adverse event during follow-up had a comparable change in PHS but a significantly smaller change in MHS, compared with those without an adverse event.Conclusions First-line ART containing NVP and/or EFV leads to an improvement in HRQoL. The gain in HRQoL was similar for NVP and EFV, but slightly lower for the combination of these drugs.

Objectives To compare the antiviral efficacy of a salvage therapy combining lopinavir and amprenavir with 200 mg/d or 400 mg/d ritonavir, together with nucleoside reverse transcriptase inhibitors, over a 26-week period in HIV-infected patients in whom multiple anti-retroviral regimens had failed.Design Phase IIb, randomized, open-label, multicentre trial. Patients were eligible if they had <500 CD4+ cells/mm3and >4 log10copies/ml HIV-RNA after treatment with at least two protease inhibitors (PIs) and one non-nucleoside reverse transcriptase inhibitor.Results At baseline (n=37), the median CD4+ cell count was 207/mm3and the median plasma HIV-1 RNA level was 4.7 log10copies/ml; the median number of PI mutations was seven and the median decrease in phenotypic susceptibility to lopinavir and amprenavir was 9.7 and 2.6, respectively. The mean number of antiretrovirals received prior to randomization was 7.7. The fall in the median HIV-1 RNA level at week 26 was -1.4 log10copies/ml in the 200 mg/d ritonavir group and -2.5 log10copies/ml in the 400 mg/d group (P=0.02). Viral load fell below 50 copies/ml in 32% and 61% of patients, respectively (P=0.07). After adjustment for the ritonavir dose, a smaller number of PI mutations was the only baseline characteristic associated with a better virological response at week 26. Amprenavir concentrations were significantly lower in presence of lopinavir. The lopinavir inhibitory quotient at week 6 correlated weakly with the change in the HIV-RNA level at week 26.Conclusion Combination of amprenavir, lopinavir and 400 mg/d ritonavir shows significant virological efficacy without increased toxicity in HIV-infected patients in whom multiple antiretroviral regimens have failed.

Osteoporosis has be reported to be a complication of active antiretroviral therapy of HIV infection. We studied 148 HIV‐infected men stratified according to their treatment. Our data show that these patients have an average 9% decreased BMD, irrespective of their treatment. Low body mass index and high resorption markers were associated with low bone density.

Osteoporosis has be reported to be a complication of active antiretroviral therapy of HIV infection. We studied 148 HIV‐infected men stratified according to their treatment. Our data show that these patients have an average 9% decreased BMD, irrespective of their treatment. Low body mass index and high resorption markers were associated with low bone density.Introduction:Osteoporosis has been reported in HIV‐infected (HIV+) patients, and it has been suggested that it may be linked to protease‐inhibitor treatments (PI).Materials and Methods:To assess this risk and to investigate its putative link with treatments, we compared the bone density of HIV+men, who were either receiving treatment (including PI [PI+], n= 49; without PI [PI−], n= 51) or untreated (UT, n= 48). We included 81 age‐matched control HIV‐negative (HIV−) males (age, 40 ± 8 years).Results:BMD adjusted for age (Z‐score) was lower in the HIV+patients at the lumbar spine (HIV+: −1.08 ± 1.21, HIV−: −0.06 ± 1.26, p< 0.001) and the femoral neck (HIV+: −0.39 ± 1.05, HIV−: 0.25 ± 0.87, p< 0.001). The prevalence of osteoporosis was 16% in HIV+and 4% in HIV−subjects (p< 0.01). In the HIV+subjects, the Z‐score was correlated only to body mass index (r= 0.27 at lumbar spine and 0.35 at femoral neck). Untreated HIV+patients had a negative Z‐score (−0.82 ± 1.15 for the lumbar spine), which was not different from the one of treated HIV+patients. In the PI+and PI−groups, the Z‐score did not depend on the presence of lipodystrophy or the proportion of fat in the abdomen and legs measured by DXA. Markers of bone remodeling were measured in the 132 HIV+and 35 HIV−subjects. Compared with controls, HIV+patients had lower bone alkaline phosphatase and higher urinary cross‐laps/Cr, which was negatively correlated with the Z‐score at both the femoral neck (r= −0.22) and lumbar spine (r= −0.21). TNFα was increased in untreated compared with treated HIV+subjects and was not correlated to the Z‐score.Conclusion:Our cross‐sectional study does not show any deleterious effect of the treatment but does indicate a decrease in bone density in HIV+patients irrespective of the treatment. This low bone density is in part related to the low body weight and is associated with increased bone resorption.

Objective A case definition of HIV lipodystrophy has recently been developed from a combination of clinical, metabolic and imaging/body composition variables using logistic regression methods. We aimed to evaluate whether artificial neural networks could improve the diagnostic accuracy.Methods The database of the case-control Lipodystrophy Case Definition Study was split into 504 subjects (265 with and 239 without lipodystrophy) used for training and 284 independent subjects (152 with and 132 without lipodystrophy) used for validation. Back-propagation neural networks with one or two middle layers were trained and validated. Results were compared against logistic regression models using the same information.Results Neural networks using clinical variables only (41 items) achieved consistently superior performance than logistic regression in terms of specificity, overall accuracy and area under the ROC curve. Their average sensitivity and specificity were 72.4 and 71.2%, as compared with 73.0 and 62.9% for logistic regression, respectively (area under the ROC curve, 0.784 vs 0.748). The discriminating performance of the neural networks was largely unaffected when built excluding 13 parameters that patients may not have readily available. The average sensitivity and specificity of the neural networks remained the same when metabolic variables were also considered (total 60 items) without a clear advantage against logistic regression (overall accuracy 71.8%). The performance of networks considering also body composition variables was similar to that of logistic regression (overall accuracy 78.5% for both).Conclusions Neural networks may offer a means to improve the discriminating performance for HIV lipodystrophy, when only clinical data are available and a rapid approximate diagnostic decision is needed. In this context, information on metabolic parameters is apparently not helpful in improving the diagnosis of HIV lipodystrophy, unless imaging and body composition studies are also obtained.