The Lancet Commission on prostate cancer: planning for the surge in cases
Bibliographic record
Abstract
Executive summaryProstate cancer is the most common cancer in men in 112 countries, and accounts for 15% of cancers.In this Commission, we report projections of prostate cancer cases in 2040 on the basis of data for demographic changes worldwide and rising life expectancy.Our findings suggest that the number of new cases annually will rise from 1•4 million in 2020 to 2•9 million by 2040.This surge in cases cannot be prevented by lifestyle changes or public health interventions alone, and governments need to prepare strategies to deal with it.We have projected trends in the incidence of prostate cancer and related mortality (assuming no changes in treatment) in the next 10-15 years, and make recom mendations on how to deal with these issues.For the Commission, we established four working groups, each of which examined a different aspect of prostate cancer: epidemiology and future projected trends in cases, the diagnostic pathway, treatment, and management of advanced disease, the main problem for most men diagnosed with prostate cancer worldwide.Throughout we have separated problems in highincome countries (HICs) from those in lowincome and middle income countries (LMICs), although we acknowledge that this distinction can be an oversimplification (some rich patients in LMICs can access highquality care, whereas many patients in HICs, especially the USA, cannot because of inadequate insurance coverage).The burden of disease globally is already substantial, but options to improve care are already available at moderate cost.We found that late diagnosis is widespread worldwide, but especially in LMICs, where it is the norm.Early diagnosis improves prognosis and outcomes, and reduces societal and individual costs, and we recommend changes to the diagnostic pathway that can be immediately implemented.For men diagnosed with advanced disease, optimal use of available technologies, adjusted to the resource levels available, could produce improved outcomes.We also found that demographic changes (ie, changing age structures and increasing life expectancy) in LMICs will drive big increases in prostate cancer, and cases are also projected to rise in highincome countries.This projected rise in cases has driven the main thrust of our recommendations throughout.Dealing with this rise in cases will require urgent and radical interventions, particularly in LMICs, including an emphasis on education (both of health professionals and the general population) linked to outreach programmes to increase awareness.If implemented, these inter ventions would shift the case mix from advanced to earlierstage disease, which in turn would necessitate different treatment approaches: earlier diagnosis would prompt a shift from palliative to curative therapies based around surgery and radiotherapy.Although ageadjusted mortality from prostate cancer is falling in HICs, it is rising in LMICs.And, despite large, well known differences in disease incidence and mortality by ethnicity (eg, incidence in men of African heritage is roughly double that in men of European heritage), most prostate cancer research has disproportionally focused on men of European heritage.
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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 | 0.028 | 0.122 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.015 | 0.012 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.023 | 0.021 |
| Insufficient payload (model declined to judge) | 0.028 | 0.020 |
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".