Psychosocial Consequences of Overdiagnostic of Prostate Cancer
Bibliographic record
Abstract
Psychosocial Consequences of Overdiagnostic of Prostate Cancer Sigrid Brisson Nielsen & John Brodersen Introduction In Denmark there are approximately 4400 men diagnosed with prostate cancer each year and nearly 1200 men dies of this disease yearly. The incidence of prostate cancer has increased for the past twenty years and make up 24 % of all cancer incidents in men. However, the mortality of prostate cancer has not changed in line with this increase. Empirical evidence shows that the increase in incidence of prostate cancer in Denmark without an increase in the mortality is mostly caused by opportunistic PSA screening in General Practice. It is recommended that men ≥ 60 year old diagnosed with prostate cancer and a Gleason score ≤ 6 are monitored with active surveillance. This is due to the probability of this type of cancer metastasizing is very small as approximately 90 % of them is assumed to be overdiagnosed. The purpose of active surveillance described above is to spare patients from sequlae due to possible overtreatment. The problem with this approach is that there can be severe negative psychosocial consequences with being overdiagnosed with prostate cancer. In international literature a Canadian qualitative study from 2000 and an American qualitative study from 2005 has been identified. However, the Canadian study focused on developing a classification system and the US study explored the effect of a psychosocial intervention. There are several quantitative studies trying to examine whether men diagnosed with prostate cancer experiences psychosocial consequences. The problem with most of the quantitative studies is that they have used questionnaires with low content validity and they have not investigated the questionnaires’ statistical measurement properties (psychometrics). Aim The aim of this study was to examine qualitative which psychosocial consequences men diagnosed with prostate cancer Gleason score ≤ 6 who is under active surveillance experiences. The informants was divided into three sub groups. The first group was men <75 years who were followed in Active Surveillance. The next group was men with an expected remaining lifetime of 10-15 years typically >70-75 years, who were followed in Watchfull Waiting. The last group was men that clinically belonged to one of the previous mentioned groups, but who insisted on active treatment despite medical advice. Methods Semi-structured qualitative interviews was conducted. The interviews was audio-recorded and transcribed. The interview data was read and coded using Strauss and Corbin’s (1998) concept of open -, axial -, and selective coding, which identify core themes, generally shared in all interviews, forming the basis of the findings section. Results and Conclusions Will be presented at the conference.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
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".