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- Abe, O, et al.
(författare)
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Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials
- 2005
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Ingår i: The Lancet. - 1474-547X. ; 365:9472, s. 1687-1717
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Tidskriftsartikel (refereegranskat)abstract
- Background Quinquennial overviews (1985-2000) of the randomised trials in early breast cancer have assessed the 5-year and 10-year effects of various systemic adjuvant therapies on breast cancer recurrence and survival. Here, we report the 10-year and 15-year effects. Methods Collaborative meta-analyses were undertaken of 194 unconfounded randomised trials of adjuvant chemotherapy or hormonal therapy that began by 1995. Many trials involved CMF (cyclophosphamide, methotrexate, fluorouracil), anthracycline-based combinations such as FAC (fluorouracil, doxombicin, cyclophosphamide) or FEC (fluorouracil, epirubicin, cyclophosphamide), tamoxifen, or ovarian suppression: none involved taxanes, trastuzumab, raloxifene, or modem aromatase inhibitors. Findings Allocation to about 6 months of anthracycline-based polychemotherapy (eg, with FAC or FEC) reduces the annual breast cancer death rate by about 38% (SE 5) for women younger than 50 years of age when diagnosed and by about 20% (SE 4) for those of age 50-69 years when diagnosed, largely irrespective of the use of tamoxifen and of oestrogen receptor (ER) status, nodal status, or other tumour characteristics. Such regimens are significantly (2p=0 . 0001 for recurrence, 2p<0 . 00001 for breast cancer mortality) more effective than CMF chemotherapy. Few women of age 70 years or older entered these chemotherapy trials. For ER-positive disease only, allocation to about 5 years of adjuvant tamoxifen reduces the annual breast cancer death rate by 31% (SE 3), largely irrespective of the use of chemotherapy and of age (<50, 50-69, &GE; 70 years), progesterone receptor status, or other tumour characteristics. 5 years is significantly (2p<0 . 00001 for recurrence, 2p=0 . 01 for breast cancer mortality) more effective than just 1-2 years of tamoxifen. For ER-positive tumours, the annual breast cancer mortality rates are similar during years 0-4 and 5-14, as are the proportional reductions in them by 5 years of tamoxifen, so the cumulative reduction in mortality is more than twice as big at 15 years as at 5 years after diagnosis. These results combine six meta-analyses: anthracycline-based versus no chemotherapy (8000 women); CMF-based versus no chemotherapy (14 000); anthracycline-based versus CMF-based chemotherapy (14 000); about 5 years of tamoxifen versus none (15 000); about 1-2 years of tamoxifen versus none (33 000); and about 5 years versus 1-2 years of tamoxifen (18 000). Finally, allocation to ovarian ablation or suppression (8000 women) also significantly reduces breast cancer mortality, but appears to do so only in the absence of other systemic treatments. For middle-aged women with ER-positive disease (the commonest type of breast cancer), the breast cancer mortality rate throughout the next 15 years would be approximately halved by 6 months of anthracycline-based chemotherapy (with a combination such as FAC or FEC) followed by 5 years of adjuvant tamoxifen. For, if mortality reductions of 38% (age <50 years) and 20% (age 50-69 years) from such chemotherapy were followed by a further reduction of 31% from tamoxifen in the risks that remain, the final mortality reductions would be 57% and 45%, respectively (and, the trial results could well have been somewhat stronger if there had been full compliance with the allocated treatments). Overall survival would be comparably improved, since these treatments have relatively small effects on mortality from the aggregate of all other causes. Interpretation Some of the widely practicable adjuvant drug treatments that were being tested in the 1980s, which substantially reduced 5-year recurrence rates (but had somewhat less effect on 5-year mortality rates), also substantially reduce 15-year mortality rates. Further improvements in long-term survival could well be available from newer drugs, or better use of older drugs.
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- Maaroos, M., et al.
(författare)
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Preventive Strategies for Atrial Fibrillation after Cardiac Surgery in Nordic Countries
- 2013
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Ingår i: Scandinavian Journal of Surgery. - : SAGE Publications. - 1457-4969 .- 1799-7267. ; 102:3, s. 178-181
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Tidskriftsartikel (refereegranskat)abstract
- Background and Aims: Atrial fibrillation is a common arrhythmia after cardiac surgery. It increases morbidity, length of hospital stay, and costs of operative treatment. Betablockers, sotalol, amiodarone, corticosteroids, and biatrial pacing have been shown to be efficient in the prevention of postoperative atrial fibrillation. The aim of this study was to find out how widely different prophylactic strategies for postoperative atrial fibrillation are used in Scandinavian countries. Material and Methods: An online link for a questionnaire was emailed to (214) cardiac surgeons in Finland, Sweden, Norway, Denmark, and Estonia to assess the use of prophylactic methods for postoperative atrial fibrillation. Results: A total of 97 surgeons responded to the survey. Oral beta-blockers were routinely used for atrial fibrillation prophylaxis by 62% of responders. The main reasons for nonuse of beta-blockers were that responders were unconvinced of the evidence of benefit or they preferred some alternative prophylaxis. Intravenous beta-blockers were used frequently by 6% of responders. Amiodarone was used for prophylaxis by 18% of responders. Nonusers were unconvinced of its efficacy, were afraid of its complications, or found its use too cumbersome. Other prophylactic atrial fibrillation strategies that were used are as follows: sotalol by 2%, magnesium by 17%, corticosteroids by 1%, and atrial pacing by 11% of respondents. Conclusions: There is still widely varying implementation of strategies for atrial fibrillation prophylaxis among Scandinavian cardiac surgeons. Lack of confidence in the efficacy of these approaches is the main rationale for nonimplementation.
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- Monteiro, Leonardo A., et al.
(författare)
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Potential Use of Data-Driven Models to Estimate and Predict Soybean Yields at National Scale in Brazil
- 2022
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Ingår i: International Journal of Plant Production. - : Springer Science and Business Media LLC. - 1735-8043 .- 1735-6814. ; 16:4, s. 691-703
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Tidskriftsartikel (refereegranskat)abstract
- Large-scale assessment of crop yields plays a fundamental role for agricultural planning and to achieve food security goals. In this study, we evaluated the robustness of data-driven models for estimating soybean yields at 120 days after sow (DAS) in the main producing regions in Brazil; and evaluated the reliability of the “best” data-driven model as a tool for early prediction of soybean yields for an independent year. Our methodology explicitly describes a general approach for wrapping up publicly available databases and build data-driven models (multiple linear regression—MLR; random forests—RF; and support vector machines—SVM) to predict yields at large scales using gridded data of weather and soil information. We filtered out counties with missing or suspicious yield records, resulting on a crop yield database containing 3450 records (23 years × 150 “high-quality” counties). RF and SVM had similar results for calibration and validation steps, whereas MLR showed the poorest performance. Our analysis revealed a potential use of data-driven models for predict soybean yields at large scales in Brazil with around one month before harvest (i.e. 90 DAS). Using a well-trained RF model for predicting crop yield during a specific year at 90 DAS, the RMSE ranged from 303.9 to 1055.7 kg ha–1 representing a relative error (rRMSE) between 9.2 and 41.5%. Although we showed up robust data-driven models for yield prediction at large scales in Brazil, there are still a room for improving its accuracy. The inclusion of explanatory variables related to crop (e.g. growing degree-days, flowering dates), environment (e.g. remotely-sensed vegetation indices, number of dry and heat days during the cycle) and outputs from process-based crop simulation models (e.g. biomass, leaf area index and plant phenology), are potential strategies to improve model accuracy.
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