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Fundamento. Adjuvant. Online calcula el riesgo de recidiva y muerte a 10 años y proporciona estimaciones del beneficio del tratamiento adyuvante en pacientes con cáncer de mama. Testamos su aplicabilidad y analizamos únicamente estimaciones de mortalidad. Método. Presentamos las estimaciones de 66 pacientes intervenidas de cáncer de mama unilateral y unicéntrico, sin enfermedad residual ni metástasis. Las variables analizadas fueron edad, comorbilidad, receptores de estrógenos, grado histológico, tamaño tumoral, ganglios metastásicos, tipo de tratamiento hormonal y de quimioterapia. Resultados. La estimación de la mediana de supervivencia fue del 77%, de mortalidad por cáncer fue del 18% y por otras causas fue del 5%. La media de reducción absoluta del riesgo (RAR) de mortalidad con tratamiento hormonal fue del 4%, con quimioterapia fue del 4,5% y con tratamiento combinado fue del 7%. Resultados. Todas las pacientes con algún beneficio decidieron recibir tratamiento hormonal. Cuarenta y tres pacientes (65%) decidieron recibir quimioterapia y 23 pacientes (35%) decidieron no recibirla. La media de reducción del riesgo con quimioterapia fue del 2% en quien decidió no recibir quimioterapia y fue del 8% en quien decidió recibirla. Existe asociación entre la decisión de quimioterapia y la estimación del riesgo de mortalidad por cáncer (p=0,0001), del riesgo de mortalidad por otras causas (p=0,038) y de la RAR (p=0,0001). El 6% de las pacientes con RAR del 1%, el 50% de las que tenían RAR entre el 2–5%, y el 61,8% con RAR entre el 6–10% eligieron la quimioterapia. Conclusiones. Todas las mujeres optan por el tratamiento hormonal independientemente del beneficio. Las razones para elegir la quimioterapia fueron el propio pronóstico vital y la magnitud del beneficio. Algunas pacientes deciden elegir quimioterapia con beneficios mínimos(AU)

Background. Adjuvant. Online estimates 10-year recurrence and mortality outcomes for breast cancer patients and predicts the effect of each type of treatment. Our purpose was to test the applicability by only analysing mortality estimations. Method. We present estimations of 66 women with definitive surgery and axillary staging for unilateral, unicentric, invasive adenocarcinoma, without metastatic or residual disease. Age, co-morbidity, estrogen receptor status, histological grade, tumor size, number of positive nodes, and hormone therapy or chemotherapy option, were the variables required. Results. Median of survival estimations was 77%, cancer mortality 18% and mortality for other reasons 5%. The average of absolute risk reduction (ARR) with hormone therapy was 4%, with chemotherapy 4.5% and with combined treatment 7%. Results. All the patients with some benefit decided to receive hormone therapy. Forty-three patients (65%) decided to receive chemotherapy and 23 (35%) did not. The average risk reduction with chemotherapy was 2% in those who decided not to receive chemotherapy and 8% in those who decided to receive it. There was an association between a chemotherapy decision and the estimation of the risk of breast cancer mortality (P=0.0001), risk of mortality for other reasons (P=0.038), and the ARR (P=0.0001). There were 6% of the patients with an ARR of 1%, 50% between 2–5% and 61.8% between 6–10%, who chose chemotherapy. Conclusions. All women opted for hormone therapy regardless of benefit. The reasons for choosing chemotherapy were the prognosis itself and the magnitude of benefit. Some patients decided to choose chemotherapy even when the benefit was minimal(AU)

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BACKGROUND: Adjuvant! Online estimates 10-year recurrence and mortality outcomes for breast cancer patients and predicts the effect of each type of treatment. Our purpose was to test the applicability by only analysing mortality estimations. METHOD: We present estimations of 66 women with definitive surgery and axillary staging for unilateral, unicentric, invasive adenocarcinoma, without metastatic or residual disease. Age, co-morbidity, estrogen receptor status, histological grade, tumor size, number of positive nodes, and hormone therapy or chemotherapy option, were the variables required. RESULTS: Median of survival estimations was 77%, cancer mortality 18% and mortality for other reasons 5%. The average of absolute risk reduction (ARR) with hormone therapy was 4%, with chemotherapy 4.5% and with combined treatment 7%. All the patients with some benefit decided to receive hormone therapy. Forty-three patients (65%) decided to receive chemotherapy and 23 (35%) did not. The average risk reduction with chemotherapy was 2% in those who decided not to receive chemotherapy and 8% in those who decided to receive it. There was an association between a chemotherapy decision and the estimation of the risk of breast cancer mortality (P=0.0001), risk of mortality for other reasons (P=0.038), and the ARR (P=0.0001). There were 6% of the patients with an ARR of 1%, 50% between 2-5% and 61.8% between 6-10%, who chose chemotherapy. CONCLUSIONS: All women opted for hormone therapy regardless of benefit. The reasons for choosing chemotherapy were the prognosis itself and the magnitude of benefit. Some patients decided to choose chemotherapy even when the benefit was minimal.

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OBJECTIVES: The authors sought to evaluate the impact of computerised chemotherapy prescription on the reduction of medication errors. The purpose of this study was to assess the incidence of errors present in electronic versus manual prescription. MATERIAL AND METHODS: The data gathered from computerised chemotherapy prescription sheets were submitted to a prospective analysis as cases of the intervention groups. The control group was comprised of the handwritten chemotherapy prescription sheets. Chemotherapy prescriptions for consecutive oncology patients were analysed by 2 independent examiners, who investigated errors of omission, commission, interpretation of dates, abbreviations and illegible handwriting. The proportion of treatment prescriptions containing one or more errors and the median of errors were calculated in order in both groups. RESULTS: At least one error was detected in 100% of the manual prescriptions and in 13% of computerised prescriptions (p < 0.001). The median of errors per computerised prescription was 0 (range: 0- 1), whereas in manual prescriptions the median was 5 (range: 1-12) (p < 0.001). Errors of omission were predominant in manual prescriptions. Errors of commission were limited to 1 case of unjustified cytostatic agent infra-dosage in a computerised prescription. This error was present in 3 cases in handwritten prescriptions and, in addition, 1 case of premedication drug substitution was detected. Errors of interpretation of the date, use of abbreviations and illegible handwriting were frequent among manual prescriptions and were absent from computerised prescriptions. CONCLUSIONS: Electronic chemotherapy prescription is a powerful tool. In this study it has been shown to decrease chemotherapy-related medication errors and ensure that safe chemotherapy practices were followed (AU)

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