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Practice and perspectives in the validation of resource management models.

ABSTRACT: Quantitative modelling is commonly used to assist the policy dimension of sustainability problems. Validation is an important step to make models credible and useful. To investigate existing validation viewpoints and approaches, we analyse a broad academic literature and conduct a survey among practitioners. We find that empirical data plays an important role in the validation practice in all main areas of sustainability science. Qualitative and participatory approaches that can enhance usefulness and public reliability are much less visible. Data-oriented validation is prevalent even when models are used for scenario exploration. Usefulness regarding a given task is more important for model developers than for users. As the experience of modellers and users increases, they tend to better acknowledge the decision makers' demand for clear communication of assumptions and uncertainties. These findings provide a reflection on current validation practices and are expected to facilitate communication at the modelling and decision-making interface.

SUBMITTER: Eker S

PROVIDER: S-EPMC6299083 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Practice and perspectives in the validation of resource management models.

Eker Sibel S Rovenskaya Elena E Obersteiner Michael M Langan Simon S

Nature communications 20181218 1

Quantitative modelling is commonly used to assist the policy dimension of sustainability problems. Validation is an important step to make models credible and useful. To investigate existing validation viewpoints and approaches, we analyse a broad academic literature and conduct a survey among practitioners. We find that empirical data plays an important role in the validation practice in all main areas of sustainability science. Qualitative and participatory approaches that can enhance usefulne ...[more]

PMID: 30560876

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Project description:To provide evidence-based, resource-stratified global recommendations to clinicians and policymakers on the management and palliative care of women diagnosed with invasive cervical cancer.ASCO convened a multidisciplinary, multinational panel of cancer control, medical and radiation oncology, health economic, obstetric and gynecologic, and palliative care experts to produce recommendations reflecting resource-tiered settings. A systematic review of literature from 1966 to 2015 failed to yield sufficiently strong quality evidence to support basic- and limited-resource setting recommendations; a formal consensus-based process was used to develop recommendations. A modified ADAPTE process was also used to adapt recommendations from existing guidelines.Five existing sets of guidelines were identified and reviewed, and adapted recommendations form the evidence base. Eight systematic reviews, along with cost-effectiveness analyses, provided indirect evidence to inform the consensus process, which resulted in agreement of 75% or greater.Clinicians and planners should strive to provide access to the most effective evidence-based antitumor and palliative care interventions. If a woman cannot access these within her own or neighboring country or region, she may need to be treated with lower-tier modalities, depending on capacity and resources for surgery, chemotherapy, radiation therapy, and supportive and palliative care. For women with early-stage cervical cancer in basic settings, cone biopsy or extrafascial hysterectomy may be performed. Fertility-sparing procedures or modified radical or radical hysterectomy may be additional options in nonbasic settings. Combinations of surgery, chemotherapy, and radiation therapy (including brachytherapy) should be used for women with stage IB to IVA disease, depending on available resources. Pain control is a vital component of palliative care. Additional information is available at www.asco.org/rs-cervical-cancer-treatment-guideline and www.asco.org/guidelineswiki. It is the view of ASCO that health care providers and health care system decision makers should be guided by the recommendations for the highest stratum of resources available. The guideline is intended to complement but not replace local guidelines.

Project description:Prediction models for population-based screening need, for global usage, to be resource-driven, involving predictors that are affordably resourced. Here, we report the development and validation of three resource-driven risk models to identify people with type 2 diabetes (T2DM) at risk of stage 3 CKD defined by a decline in estimated glomerular filtration rate (eGFR) to below 60 mL/min/1.73m2. The observational study cohort used for model development consisted of data from a primary care dataset of 20,510 multi-ethnic individuals with T2DM from London, UK (2007-2018). Discrimination and calibration of the resulting prediction models developed using cox regression were assessed using the c-statistic and calibration slope, respectively. Models were internally validated using tenfold cross-validation and externally validated on 13,346 primary care individuals from Wales, UK. The simplest model was simplified into a risk score to enable implementation in community-based medicine. The derived full model included demographic, laboratory parameters, medication-use, cardiovascular disease history (CVD) and sight threatening retinopathy status (STDR). Two less resource-intense models were developed by excluding CVD and STDR in the second model and HbA1c and HDL in the third model. All three 5-year risk models had good internal discrimination and calibration (optimism adjusted C-statistics were each 0.85 and calibration slopes 0.999-1.002). In Wales, models achieved excellent discrimination(c-statistics ranged 0.82-0.83). Calibration slopes at 5-years suggested models over-predicted risks, however were successfully updated to accommodate reduced incidence of stage 3 CKD in Wales, which improved their alignment with the observed rates in Wales (E/O ratios near to 1). The risk score demonstrated similar model performance compared to direct evaluation of the cox model. These resource-driven risk prediction models may enable universal screening for Stage 3 CKD to enable targeted early optimisation of risk factors for CKD.

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Practice and perspectives in the validation of resource management models.

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Practice and perspectives in the validation of resource management models.

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