A Patient Advocacy Group Summit, Cancer Care in Turkey and The Society of Breast Health
Bibliographic record
Abstract
According to the World Health Organization (WHO), cancer now causes more deaths than all cardiac or all other diseases (1).The number of new cases is expected to rise by about 70% over the next 2 decades.Globally, nearly 1 in 6 deaths is due to cancer, and approximately 70% of deaths from cancer occur in low-and middle-income countries (2).There is a significant disparity in cancer care and outcome of cancer patient results between developed and developing countries.The most important aims of cancer management are prevention, screening, early detection, and effective treatment.In addition to the health care system, patients are the most important stakeholders of cancer care.Patient advocacy groups (PAG) are non-profit, non-governmental (NGO) organizations, and they may play an important role to acquire and protect patients' rights for better cancer management.PAGs can incorporate cancer scientists in a way similar to The Society of Breast Health to perform basic, reliable, and reasonable clinical projects based on the economic, socio-cultural and educational structure of a country.The number of PAGs should be increased and representatives of them should be participated in governmental organizations (such as National cancer Advisory Board, National Cancer Institute, etc.) to advocate and acquire their rights.Their participation absolutely provides integrity in health care systems.To be a more effective and powerful part of cancer care, PAGs should come together in national and international platforms to share their problems and find solutions.Additionally, expert panelists in this field may explain more useful solutions to increase the benefit of these summits.There was an important patient advocacy group (PAG) summit in Vienna on 15-16, September, 2017.I would like to share my views and opinions about this summit as an invited speaker.Twenty-three delegates from 22 patient-groups representing 17 Central and Eastern European (CEE) countries and seven international experts came together at a first-of-its-kind oncology summit (Figure 1).The aims of the summit were to learn from each other about how to improve cancer care through advocacy in their countries, and to inform, empower and equip patient groups so that they are better able to address the challenges they face.The meeting also encouraged relationship-building and the strengthening of peer-to-peer networks between groups and countries.The summit objectives were below:• Bring together the cancer patient community to encourage sharing of experiences and ideas • Facilitate dialogue and learning about capacity building, communications and effective cancer policy campaigning • Inform the community about relevant developments in cancer and global standards • Empower patient advocates to take on old challenges with new insight • Equip organisation with new skills and knowledge to be more effective.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.011 | 0.012 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".