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Survivorship: Improving the ‘Handoff’

2010· article· en· W2334287982 on OpenAlexaboutno aff
Robert H. Carlson

Bibliographic record

VenueOncology Times · 2010
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsnot available
Fundersnot available
KeywordsSurvivorship curveGuidelineSession (web analytics)MedicineHealth careFamily medicineCancer survivorCancerNursingPolitical science

Abstract

fetched live from OpenAlex

CHICAGO—As more cancer survivors achieve long-term remission, the challenges of survivorship care—i.e., caring for patients after cancer treatment has ended—become greater for most oncologists. One challenge discussed here at the ASCO Annual Meeting in a special session is the difficulty of segueing from management of cancer to long-term patient care. Fumbling the Handoff The survivorship issue is relatively new to ASCO, noted Douglas Blayney, MD, ASCO’s 2009-10 President. The Annual Meeting has had sessions devoted to survivorship only since 2003, when the grand total of information devoted to that topic was one Education Session. In contrast, this year’s meeting had 14 sessions devoted to aspects of survivorship, including three Patient and Survivor Care abstract sessions. Dr. Blayney said that ASCO is well aware that there are shortcomings in resources oncologists can call on in the transition from cancer treatment to survivorship care. He called this a “fumbled handoff,” to use a football term, when there is poor coordination of cancer care among oncologists, primary care physicians, nurses, and other health care providers. There is a lack of a solid knowledge base to support follow-up care guidelines—”It turns out that there is not enough high-quality evidence demonstrating the optimal use of patients’ and physicians’ time and resources,” he said. Guideline-Development Process ASCO’s guideline-development process is reliant on high-quality randomized clinical trial evidence, but when the Society tried to apply that mechanism, looking for evidence and surveillance on cardiac, pulmonary, or fertility problems cancer survivors may have, the data were not there. “We’ve published guidelines on fertility preservation, but the cardiovascular and pulmonary guideline panel work did not result in formal ASCO guidelines, and neither did the hormone-deficiency panel,” he said. Secondary malignancies and psychosocial effects in long-term survivors are also areas where additional guidance is needed. “There is a paucity of evidence from controlled, clinical trials, and ASCO needs to reexamine the ‘guideline’ process in survivorship. “Our current process does not allow us to produce guidelines for this kind of treatment in survivorship,” he continued. Added to that is a lack of evidence-based cancer-prevention strategies. In answer to this, Dr. Blayney said ASCO is promoting survivorship care research in its journals, enhancing survivorship in its scientific programs to include survivorship tracks, and strengthening representation for survivorship on the scientific program committees. Currently there are ASCO treatment plans and summary templates for breast cancer, colon cancer, non-small-cell lung cancer, small-cell lung cancer, and lymphoma, as well as a generic plan. Poorly Equipped, in Short Supply Dr. Blayney said ASCO studies have shown that oncologists, particularly radiation oncologists and surgeons, are poorly equipped, or in short supply, to make meaningful interventions. “People of our generation were not trained to deal with survivors,” he said. Meanwhile, “cardiologists and pulmonologists don’t see themselves involved in long-term care of cancer survivors, not until the patient actually develops symptomatic problems,” he said. “Surveillance on long-term cancer survivors is not what the other physicians want to do.” Guidelines from other medical specialties, such as cardiology and pulmonology, have not been that useful in drafting oncology survivorship guidelines, he said. “The oncologist is the best equipped of anybody to know what’s going on [in survivorship]. But even for oncologists who have an interest in—and at many times a personal relationship with—long-term survivors, our equipment needs to be better.” Key Questions Dr. Blayney listed some of the important questions that need to be addressed: What impact does the expansion of survivorship services have on the oncology business model? When do patients “graduate” from oncology care? This is highly variable, he said, depending to a great extent on geography and proximity to the medical provider. Who will provide this long-term care? Dr. Blayney said baseline projections reveal significant provider shortages by the year 2020. Cancer survivors are a homogeneous lot, and while survivors age 70 and older not surprisingly make up about 50% of the total, 22% are age 60 to 69, 16% are 50 to 59; 8% are 40 to 49, 4% are 30 to 39%, and 1% are 29 and younger, he said—”And each of these groups has their own survivorship issues.” DOUGLAS BLAYNEY, MD, said that although ASCO has published guidelines on fertility preservation, the cardiovascular and pulmonary guideline panel work did not result in any formal ASCO guidelines, and neither did the hormone-deficiency panel—”It turns out that there is not enough high-quality evidence demonstrating the optimal use of patients’ and physicians’ time and resources.”But Good News, in a Way Another speaker, Eva Grunfeld, MD, DPhil, Clinical Scientist and Director of the Knowledge Translation Research Network, Health Services Research Program, at Ontario Institute for Cancer Research, said that talking about cancer survivorship is a good news story because people are now less focused on just survival and they’re thinking about the survivorship. “It reflects the fact that the majority of people diagnosed with cancer today will be long-term survivors,” she said. “Twenty years ago, once a patient had been diagnosed with cancer or after treatment was completed, we were focused on their survival. “Now we’re concerned with survivorship—their quality of life and other medical conditions that need attention. And we’re aware that they are candidates for other preventive maneuvers.”

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.849
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.013
GPT teacher head0.288
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

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Citations0
Published2010
Admission routes1
Has abstractyes

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