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- Fitzmauric, C., et al.
(författare)
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Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived with Disability, and Disability-Adjusted Life-Years for 29 Cancer Groups, 1990 to 2017 : A Systematic Analysis for the Global Burden of Disease Study
- 2019
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Ingår i: JAMA Oncology. - : American Medical Association. - 2374-2437 .- 2374-2445. ; 5:12, s. 1749-1768
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Tidskriftsartikel (refereegranskat)abstract
- Importance: Cancer and other noncommunicable diseases (NCDs) are now widely recognized as a threat to global development. The latest United Nations high-level meeting on NCDs reaffirmed this observation and also highlighted the slow progress in meeting the 2011 Political Declaration on the Prevention and Control of Noncommunicable Diseases and the third Sustainable Development Goal. Lack of situational analyses, priority setting, and budgeting have been identified as major obstacles in achieving these goals. All of these have in common that they require information on the local cancer epidemiology. The Global Burden of Disease (GBD) study is uniquely poised to provide these crucial data.Objective: To describe cancer burden for 29 cancer groups in 195 countries from 1990 through 2017 to provide data needed for cancer control planning.Evidence Review: We used the GBD study estimation methods to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life-years (DALYs). Results are presented at the national level as well as by Socio-demographic Index (SDI), a composite indicator of income, educational attainment, and total fertility rate. We also analyzed the influence of the epidemiological vs the demographic transition on cancer incidence.Findings: In 2017, there were 24.5 million incident cancer cases worldwide (16.8 million without nonmelanoma skin cancer [NMSC]) and 9.6 million cancer deaths. The majority of cancer DALYs came from years of life lost (97%), and only 3% came from years lived with disability. The odds of developing cancer were the lowest in the low SDI quintile (1 in 7) and the highest in the high SDI quintile (1 in 2) for both sexes. In 2017, the most common incident cancers in men were NMSC (4.3 million incident cases); tracheal, bronchus, and lung (TBL) cancer (1.5 million incident cases); and prostate cancer (1.3 million incident cases). The most common causes of cancer deaths and DALYs for men were TBL cancer (1.3 million deaths and 28.4 million DALYs), liver cancer (572000 deaths and 15.2 million DALYs), and stomach cancer (542000 deaths and 12.2 million DALYs). For women in 2017, the most common incident cancers were NMSC (3.3 million incident cases), breast cancer (1.9 million incident cases), and colorectal cancer (819000 incident cases). The leading causes of cancer deaths and DALYs for women were breast cancer (601000 deaths and 17.4 million DALYs), TBL cancer (596000 deaths and 12.6 million DALYs), and colorectal cancer (414000 deaths and 8.3 million DALYs).Conclusions and Relevance: The national epidemiological profiles of cancer burden in the GBD study show large heterogeneities, which are a reflection of different exposures to risk factors, economic settings, lifestyles, and access to care and screening. The GBD study can be used by policy makers and other stakeholders to develop and improve national and local cancer control in order to achieve the global targets and improve equity in cancer care.
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| 4. |
- Micah, Angela E., et al.
(författare)
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Tracking development assistance for health and for COVID-19 : a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990-2050
- 2021
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Ingår i: The Lancet. - : Elsevier. - 0140-6736 .- 1474-547X. ; 398:10308, s. 1317-1343
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Forskningsöversikt (refereegranskat)abstract
- Background The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020. Methods We estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US$, 2020 US$ per capita, purchasing-power parity-adjusted US$ per capita, and as a proportion of gross domestic product. We used various models to generate future health spending to 2050. Findings In 2019, health spending globally reached $8. 8 trillion (95% uncertainty interval [UI] 8.7-8.8) or $1132 (1119-1143) per person. Spending on health varied within and across income groups and geographical regions. Of this total, $40.4 billion (0.5%, 95% UI 0.5-0.5) was development assistance for health provided to low-income and middle-income countries, which made up 24.6% (UI 24.0-25.1) of total spending in low-income countries. We estimate that $54.8 billion in development assistance for health was disbursed in 2020. Of this, $13.7 billion was targeted toward the COVID-19 health response. $12.3 billion was newly committed and $1.4 billion was repurposed from existing health projects. $3.1 billion (22.4%) of the funds focused on country-level coordination and $2.4 billion (17.9%) was for supply chain and logistics. Only $714.4 million (7.7%) of COVID-19 development assistance for health went to Latin America, despite this region reporting 34.3% of total recorded COVID-19 deaths in low-income or middle-income countries in 2020. Spending on health is expected to rise to $1519 (1448-1591) per person in 2050, although spending across countries is expected to remain varied. Interpretation Global health spending is expected to continue to grow, but remain unequally distributed between countries. We estimate that development organisations substantially increased the amount of development assistance for health provided in 2020. Continued efforts are needed to raise sufficient resources to mitigate the pandemic for the most vulnerable, and to help curtail the pandemic for all. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.
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| 5. |
- Feigin, Valery L., et al.
(författare)
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Global, regional, and national burden of neurological disorders, 1990–2016 : a systematic analysis for the Global Burden of Disease Study 2016
- 2019
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Ingår i: Lancet Neurology. - : Elsevier. - 1474-4422 .- 1474-4465. ; 18:5, s. 459-480
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Tidskriftsartikel (refereegranskat)abstract
- Background: Neurological disorders are increasingly recognised as major causes of death and disability worldwide. The aim of this analysis from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 is to provide the most comprehensive and up-to-date estimates of the global, regional, and national burden from neurological disorders.Methods: We estimated prevalence, incidence, deaths, and disability-adjusted life-years (DALYs; the sum of years of life lost [YLLs] and years lived with disability [YLDs]) by age and sex for 15 neurological disorder categories (tetanus, meningitis, encephalitis, stroke, brain and other CNS cancers, traumatic brain injury, spinal cord injury, Alzheimer's disease and other dementias, Parkinson's disease, multiple sclerosis, motor neuron diseases, idiopathic epilepsy, migraine, tension-type headache, and a residual category for other less common neurological disorders) in 195 countries from 1990 to 2016. DisMod-MR 2.1, a Bayesian meta-regression tool, was the main method of estimation of prevalence and incidence, and the Cause of Death Ensemble model (CODEm) was used for mortality estimation. We quantified the contribution of 84 risks and combinations of risk to the disease estimates for the 15 neurological disorder categories using the GBD comparative risk assessment approach.Findings: Globally, in 2016, neurological disorders were the leading cause of DALYs (276 million [95% UI 247–308]) and second leading cause of deaths (9·0 million [8·8–9·4]). The absolute number of deaths and DALYs from all neurological disorders combined increased (deaths by 39% [34–44] and DALYs by 15% [9–21]) whereas their age-standardised rates decreased (deaths by 28% [26–30] and DALYs by 27% [24–31]) between 1990 and 2016. The only neurological disorders that had a decrease in rates and absolute numbers of deaths and DALYs were tetanus, meningitis, and encephalitis. The four largest contributors of neurological DALYs were stroke (42·2% [38·6–46·1]), migraine (16·3% [11·7–20·8]), Alzheimer's and other dementias (10·4% [9·0–12·1]), and meningitis (7·9% [6·6–10·4]). For the combined neurological disorders, age-standardised DALY rates were significantly higher in males than in females (male-to-female ratio 1·12 [1·05–1·20]), but migraine, multiple sclerosis, and tension-type headache were more common and caused more burden in females, with male-to-female ratios of less than 0·7. The 84 risks quantified in GBD explain less than 10% of neurological disorder DALY burdens, except stroke, for which 88·8% (86·5–90·9) of DALYs are attributable to risk factors, and to a lesser extent Alzheimer's disease and other dementias (22·3% [11·8–35·1] of DALYs are risk attributable) and idiopathic epilepsy (14·1% [10·8–17·5] of DALYs are risk attributable).Interpretation: Globally, the burden of neurological disorders, as measured by the absolute number of DALYs, continues to increase. As populations are growing and ageing, and the prevalence of major disabling neurological disorders steeply increases with age, governments will face increasing demand for treatment, rehabilitation, and support services for neurological disorders. The scarcity of established modifiable risks for most of the neurological burden demonstrates that new knowledge is required to develop effective prevention and treatment strategies.Funding: Bill & Melinda Gates Foundation.
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- Gu, Xiaolian, 1976-, et al.
(författare)
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Early detection of squamous cell carcinoma of the oral tongue using multidimensional plasma protein analysis and interpretable machine learning
- 2023
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Ingår i: Journal of Oral Pathology & Medicine. - : John Wiley & Sons. - 0904-2512 .- 1600-0714. ; 52:7, s. 637-643
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Tidskriftsartikel (refereegranskat)abstract
- Background: Interpretable machine learning (ML) for early detection of cancer has the potential to improve risk assessment and early intervention.Methods: Data from 261 proteins related to inflammation and/or tumor processes in 123 blood samples collected from healthy persons, but of whom a sub-group later developed squamous cell carcinoma of the oral tongue (SCCOT), were analyzed. Samples from people who developed SCCOT within less than 5 years were classified as tumor-to-be and all other samples as tumor-free. The optimal ML algorithm for feature selection was identified and feature importance computed by the SHapley Additive exPlanations (SHAP) method. Five popular ML algorithms (AdaBoost, Artificial neural networks [ANNs], Decision Tree [DT], eXtreme Gradient Boosting [XGBoost], and Support Vector Machine [SVM]) were applied to establish prediction models, and decisions of the optimal models were interpreted by SHAP.Results: Using the 22 selected features, the SVM prediction model showed the best performance (sensitivity = 0.867, specificity = 0.859, balanced accuracy = 0.863, area under the receiver operating characteristic curve [ROC-AUC] = 0.924). SHAP analysis revealed that the 22 features rendered varying person-specific impacts on model decision and the top three contributors to prediction were Interleukin 10 (IL10), TNF Receptor Associated Factor 2 (TRAF2), and Kallikrein Related Peptidase 12 (KLK12).Conclusion: Using multidimensional plasma protein analysis and interpretable ML, we outline a systematic approach for early detection of SCCOT before the appearance of clinical signs.
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| 7. |
- Salehi, Amir M., 1971-
(författare)
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Clinical investigation and application of Artificial Intelligence in diagnosis and prognosis of squamous cell carcinoma of the head and neck
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Background: In Sweden around 1400 people are affected by head and neck cancer each year, and around 400 of these tumours are located in the mobile tongue (SCCOT). A major problem with these tumours is the high degree of relapse. In order to broaden our understanding of the group of squamous cell carcinoma of the head and neck (SCCHN) tumours we evaluated and compared the outcomes of panendoscopy with biopsy, ultrasonography with fine needle aspiration cytology (US-FNAC), and preoperative positron emission tomography/computed tomography (PET/CT) data from the same patients. As patients with SCCHN frequently have distant metastasis and locoregional recurrences, machine learning (ML) techniques were used to create classification models that accurately predict the likelihood of an early recurrence.Materials and methods: From patients suspected of having head and neck cancer between 2014–2016 results from PET/CT, panendoscopy with biopsy and US-FNAC were compared. Clinical, genomic, transcriptomic, and proteomic markers identifying recurrence risk were investigated. In blood samples taken from healthy individuals, data from proteins relevant to inflammation and/or tumor processes were evaluated. The SHapley Additive Explanations (SHAP) approach was used to determine the best ML algorithm for feature selection. AdaBoost, Artificial neural networks (ANNs), Decision Tree (DT), eXtreme Gradient Boosting (XGBoost), and Support Vector Machine (SVM) were used to create prediction models. Clinical data from patients were analyzed using statistical and ML techniques.Results: The concordance between results from PET/CT and panendoscopy with biopsy was 91.3%, and somewhat lower, 89.1%, for PET/CT and US-FNAC. The top contributors to classification with the ML approach were five mRNAs (PLAUR, DKK1, AXIN2, ANG, VEGFA), and 10 proteins (RAD50, 4E-BP1, MYH11, MAP2K1, BECN1, NF2, RAB25, ERRFI1, KDR, SERPINE1), using the extreme gradient boosting (XGBoost) method. The SHAP approach was used for feature selection. Using data from analysis of proteins in blood and interpretable ML showed that the Support Vector Machine (SVM) had the best performance with a balanced accuracy of 0.863, and a ROC-AUC of 0.924. The top three contributors to the SVM prediction model's performance were IL10, TNF Receptor Associated Factor 2 (TRAF2), and Kallikrein Related Peptidase 12 (KLK12). Recurrence was correlated with diabetes (p = 0.003), radiographic neck metastasis (p = 0.010), and T stage (p = 0.0012). A ML model got an accuracy rate of 71.2%. In the SCCOT group, diabetics predominated over non-diabetics, and also had lower recurrence rates and better survival (p = 0.012).Conclusion: Results show that the combination PET/CT is useful in diagnosis of SCCHN. It further emphasizes the use of ML to identify transcriptomic and proteomic factors that are significant in predicting risk of recurrence in patients with SCCHN. It provides a methodical strategy for early diagnosis of SCCOT before onset of clinical symptoms using multidimensional plasma protein profiling and interpretable ML. A model for predicting recurrence of SCCOT is provided by ML utilizing clinical data. As SCCOT patients with co-existing diabetes showed a better prognosis than non-diabetics, results suggest that individuals with SCCOT, regardless of diabetes status, may benefit from therapeutic management of glucose levels.
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| 8. |
- Salehi, Amir M., et al.
(författare)
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Comparison of Preoperative Positron Emission Tomography/Computed Tomography with Panscopy and Ultrasound in Patients with Head and Neck Cancer
- 2020
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Ingår i: Oncology. - : S. Karger. - 0030-2414 .- 1423-0232. ; 98:12, s. 889-892
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: To compare data from preoperative positron emission tomography/computed tomography (PET/CT) with results of panscopy with biopsy and ultrasound with fine needle aspiration cytology (US-FNAC) on the same patients.Methods: In this retrospective (2014-2016) study, we compared PET/CT results with the results from panscopy with biopsy and US-FNAC in patients suspected of head and neck malignancy treated at the University Hospital in Umea, Sweden.Results: A 91.3% concordance was seen between results from PET/CT and panscopy with biopsy, whereas between PET/CT and US-FNAC the concordance was 89.1%.Conclusions: The present data show the usefulness of PET/CT in the diagnosis of head and neck malignancies.
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| 9. |
- Salehi, Amir M., et al.
(författare)
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Comparison of Quality of Life among Patients with Oro-Hypopharyngeal Cancer after Tonsillectomy and Panscopy Using Transoral Robotic Surgery : A Pilot Study
- 2020
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Ingår i: Case Reports in Oncology. - : S. Karger. - 1662-6575. ; 13:3, s. 1295-1303
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Tidskriftsartikel (refereegranskat)abstract
- Studies have shown lower treatment-related morbidity when using transoral robotic surgery (TORS) compared to conventional surgery. Patients investigated for oro- and hypopharyngeal cancer (T1, T2) were compared concerning quality of life (QoL) after tonsillectomy and TORS using validated QoL questionnaires: QLQ-C30 and QLQ-H&N35. The patients treated with TORS showed a higher pain score and thus also a higher need for painkillers, whereas they had lower values on self-assessment of anxiety/depression using the Hospital Anxiety and Depression Scale score. The pre- and postoperative information given did not meet the expectations of the patients treated with conventional surgery. The present data show advantages of the TORS technique from the patients' perspective. Even if patients treated with TORS are in need of more painkilling treatment, they cope better with the long-term effects of treatment, as judged by self-assessment of anxiety and depression.
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| 10. |
- Salehi, Amir M., et al.
(författare)
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Patients with oral tongue squamous cell carcinoma and co‑existing diabetes exhibit lower recurrence rates and improved survival : implications for treatment
- 2024
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Ingår i: Oncology Letters. - : Spandidos Publications. - 1792-1074 .- 1792-1082. ; 27:4
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Tidskriftsartikel (refereegranskat)abstract
- Locoregional recurrences and distant metastases are major problems for patients with squamous cell carcinoma of the head and neck (SCCHN). Because SCCHN is a heterogeneous group of tumours with varying characteristics, the present study concentrated on the subgroup of squamous cell carcinoma of the oral tongue (SCCOT) to investigate the use of machine learning approaches to predict the risk of recurrence from routine clinical data available at diagnosis. The approach also identified the most important parameters that identify and classify recurrence risk. A total of 66 patients with SCCOT were included. Clinical data available at diagnosis were analysed using statistical analysis and machine learning approaches. Tumour recurrence was associated with T stage (P=0.001), radiological neck metastasis (P=0.010) and diabetes (P=0.003). A machine learning model based on the random forest algorithm and with attendant explainability was used. Whilst patients with diabetes were overrepresented in the SCCOT cohort, diabetics had lower recur‑ rence rates (P=0.015 after adjusting for age and other clinical features) and an improved 2‑year survival (P=0.025) compared with non‑diabetics. Clinical, radiological and histological data available at diagnosis were used to establish a prognostic model for patients with SCCOT. Using machine learning to predict recurrence produced a classification model with 71.2% accuracy. Notably, one of the findings of the feature importance rankings of the model was that diabetics exhibited less recur‑ rence and improved survival compared with non‑diabetics, even after accounting for the independent prognostic variables of tumour size and patient age at diagnosis. These data imply that the therapeutic manipulation of glucose levels used to treatdiabetes may be useful for patients with SCCOT regardless of their diabetic status. Further studies are warranted to investigatethe impact of diabetes in other SCCHN subtypes.
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