Impacts of fire and prospects for recovery in a tropical peat forest ecosystem.

Uncontrolled fires place considerable burdens on forest ecosystems, compromising our ability to meet conservation and restoration goals. A poor understanding of the impacts of fire on ecosystems and their biodiversity exacerbates this challenge, particularly in tropical regions where few studies have applied consistent analytical techniques to examine a broad range of ecological impacts over multiyear time frames. We compiled 16 y of data on ecosystem properties (17 variables) and biodiversity (21 variables) from a tropical peatland in Indonesia to assess fire impacts and infer the potential for recovery. Burned forest experienced altered structural and microclimatic conditions, resulting in a proliferation of nonforest vegetation and erosion of forest ecosystem properties and biodiversity. Compared to unburned forest, habitat structure, tree density, and canopy cover deteriorated by 58 to 98%, while declines in species diversity and abundance were most pronounced for trees, damselflies, and butterflies, particularly for forest specialist species. Tracking ecosystem property and biodiversity datasets over time revealed most to be sensitive to recurrent high-intensity fires within the wider landscape. These megafires immediately compromised water quality and tree reproductive phenology, crashing commercially valuable fish populations within 3 mo and driving a gradual decline in threatened vertebrates over 9 mo. Burned forest remained structurally compromised long after a burn event, but vegetation showed some signs of recovery over a 12-y period. Our findings demonstrate that, if left uncontrolled, fire may be a pervasive threat to the ecological functioning of tropical forests, underscoring the importance of fire prevention and long-term restoration efforts, as exemplified in Indonesia.

Fixing the Leaky Pipe: How to Improve the Uptake of Patient-Reported Outcomes-Based Prognostic and Predictive Models in Cancer Clinical Practice.

PURPOSE: This discussion paper outlines challenges and proposes solutions for successfully implementing prediction models that incorporate patient-reported outcomes (PROs) in cancer practice. METHODS: We organized a full-day multidisciplinary meeting of people with expertise in cancer care delivery, PRO collection, PRO use in prediction modeling, computing, implementation, and decision science. The discussions presented here focused on identifying challenges to the development, implementation and use of prediction models incorporating PROs, and suggesting possible solutions. RESULTS: Specific challenges and solutions were identified across three broad areas. (1) Understanding decision making and implementation: necessitating multidisciplinary collaboration in the early stages and throughout; early stakeholder engagement to define the decision problem and ensure acceptability of PROs in prediction; understanding patient/clinician interpretation of PRO predictions and uncertainty to optimize prediction impact; striving for model integration into existing electronic health records; and early regulatory alignment. (2) Recognizing the limitations to PRO collection and their impact on prediction: incorporating validated, clinically important PROs to maximize model generalizability and clinical engagement; and minimizing missing PRO data (resulting from both structural digital exclusion and time-varying factors) to avoid exacerbating existing inequalities. (3) Statistical and modeling challenges: incorporating statistical methods to address missing data; ensuring predictive modeling recognizes complex causal relationships; and considering temporal and geographic recalibration so that model predictions reflect the relevant population. CONCLUSION: Developing and implementing PRO-based prediction models in cancer care requires extensive multidisciplinary working from the earliest stages, recognition of implementation challenges because of PRO collection and model presentation, and robust statistical methods to manage missing data, causality, and calibration. Prediction models incorporating PROs should be viewed as complex interventions, with their development and impact assessment carried out to reflect this.

Implications of large-scale infrastructure development for biodiversity in Indonesian Borneo.

Indonesia is embarking on an ambitious relocation of its capital city to Kalimantan, Borneo, bringing with it major urban and road infrastructure. Yet, despite being one of the world's most biologically diverse regions, the potential implications of this development for wildlife have yet to be fully assessed. We explored the potential impacts of the capital relocation, and road expansion and upgrades to critical habitat for medium-large mammals (>1 kg) using camera trap data from 11 forested landscapes. We applied Bayesian multi-species occupancy models to predict community and species-level responses to anthropogenic and environmental factors. We extrapolated spatial patterns of occupancy and species diversity across the forests of Kalimantan and identified "critical habitats" as the top 20th percentile of occupancy and species richness values. We subsequently overlapped these critical habitat layers with infrastructure impact zones to estimate the area that could potentially be affected by direct or secondary impacts. At both the community and species-level, distance to primary roads had the strongest negative influence on habitat-use. Occupancy was also influenced by forest quality and multidimensional poverty conditions in adjacent villages, demonstrating the sensitivity of biodiversity to socio-ecological pressures. Less than 1 % of the critical habitat for the threatened mammal community lay within the direct impact zone (30 km radius) of the capital relocation. However, approximately 16 % was located within 200 km and could potentially be affected by uncontrolled secondary impacts such as urban sprawl and associated regional development. The often-overlooked secondary implications of upgrading existing roads could also intersect a large amount of critical habitat for lowland species. Mitigating far-reaching secondary impacts of infrastructure development should be fully incorporated into environmental impact assessments. This will provide Indonesia with an opportunity to set an example of sustainable infrastructure development in the tropics.

Systematic Review of the Role of Stereotactic Radiotherapy for Bone Metastases.

BACKGROUND: Stereotactic radiotherapy (SBRT) might improve pain and local control in patients with bone metastases compared to conventional radiotherapy, although an overall estimate of these outcomes is currently unknown. METHODS: A systematic review was carried out following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Pubmed, Embase, and Cochrane databases were systematically searched to identify studies reporting pain response and local control among patients with bone metastases from solid-organ tumors who underwent SBRT in 1-6 fractions. All studies prior to April 15, 2017, were included. Study quality was assessed by predefined criteria, and pain response and local control rates were extracted. RESULTS: A total of 2619 studies were screened; 57 were included (reporting outcomes for 3995 patients) of which 38 reported pain response and 45 local control rates. Local control rates were high with pain response rates above those previously reported for conventional radiotherapy. Marked heterogeneity in study populations and delivered treatments were identified such that quantitative synthesis was not appropriate. Reported toxicity was limited. Of the pain response studies, 73.7% used a retrospective cohort design and only 10.5% used the international consensus endpoint definitions of pain response. The median survival within the included studies ranged from 8 to 30.4 months, suggesting a high risk of selection bias in the included observational studies. CONCLUSIONS: This review demonstrates the potential benefit of SBRT over conventional palliative radiotherapy in improving pain due to bone metastases. Given the methodological limitations of the published literature, however, large randomized trials are now urgently required to better quantify this benefit.

Surgery or radiotherapy for stage I lung cancer? An intention-to-treat analysis.

INTRODUCTION: Surgery is the standard of care for early-stage lung cancer, with stereotactic ablative body radiotherapy (SABR) a lower morbidity alternative for patients with limited physiological reserve. Comparisons of outcomes between these treatment options are limited by competing comorbidities and differences in pre-treatment pathological information. This study aims to address these issues by assessing both overall and cancer-specific survival for presumed stage I lung cancer on an intention-to-treat basis. METHODS: This retrospective intention-to-treat analysis identified all patients treated for presumed stage I lung cancer within a single large UK centre. Overall survival, cancer-specific survival, and combined cancer and treatment-related survival were assessed with adjustment for confounding variables using Cox proportional hazards and Fine-Gray competing risks analyses. RESULTS: 468 patients (including 316 surgery and 99 SABR) were included in the study population. Compared with surgery, SABR was associated with inferior overall survival on multivariable Cox modelling (SABR HR 1.84 (95% CI 1.32-2.57)), but there was no difference in cancer-specific survival (SABR HR 1.47 (95% CI 0.80-2.69)) or combined cancer and treatment-related survival (SABR HR 1.27 (95% CI 0.74-2.17)). Combined cancer and treatment-related death was no different between SABR and surgery on Fine-Gray competing risks multivariable modelling (subdistribution hazard 1.03 (95% CI 0.59-1.81)). Non-cancer-related death was significantly higher in SABR than surgery (subdistribution hazard 2.16 (95% CI 1.41-3.32)). CONCLUSION: In this analysis, no difference in cancer-specific survival was observed between SABR and surgery. Further work is needed to define predictors of outcome and help inform treatment decisions.