Bibliographic record
Abstract
P RIMARY CARE physicians shouldnot be routinely screening for prostate cancer. There is no conclusive evidence that screening is effective in reducing prostate cancer morbidity and mortality, but there is considerable evidence that screening and treatment can be harmful. Primary care physicians should routinely discuss screening, but patients need to make an informed decision to be screened. Prostate cancer is an important public health problem—a devastating disease that was expected to have killed more than 30000 American men in 2002. Unfortunately, our current prevention and treatment strategies are limited in their ability to reduce the burden of suffering from prostate cancer.Thestrongest risk factors are age, race, and family history, none of which can be modified. Although dietary micronutrients, antioxidant vitamins, and finasteride are being studied for the primary prevention of prostate cancer, we currently have no proven prevention strategy. Men with advanced cancers can be treated only with palliative therapy. Consequently, therehasbeengreat interest in detecting prostate cancers at an early, asymptomatic stage, especially since the discovery of PSA. The hope is that detecting early stage cancers and treating them aggressively with surgery or radiation will reduce morbidity and mortality from prostate cancer. The American Urologic Association and the American Cancer Society support routine screening for prostate cancer using PSA and DRE. However, other professional organizations, such as the American College of Physicians–American Society of Internal Medicine and the US Preventive Services Task Force recommend against routine screening. Why is there controversy over screening? One reason is that the evidence supporting the benefit of screening is only indirect. Since the advent of PSA testing, there has been a stage shift in cancers at diagnosis, away from advanced-stage and toward early-stage disease. However, demonstrating a stage shift alone is not sufficient proof that screening is effective. Another important criterion for assessing a screening program is reduced mortality. Prostate cancer mortality rates sharply increased in the early 1990s before declining. Mortality rates are now slightly lower than they were before PSA testing was introduced. However, this decline may not reflect a benefit of screening. Better palliative treatmentsareavailable, andmenwith advanced-stage cancers, who are often elderly, may now live long enough to die from competing comorbidities. Feuer and colleagues have also argued that attribution bias (ie, erroneously assigning prostate cancer as the cause of death on death certification) could explain some of the trends inmortality rates.Prostate-specific antigen testing began in the late 1980s and led to an increase in the incidence of prostate cancer. Consequently, there would have been a larger pool of men with prostate cancer whose deaths might have been attributed to prostate cancer. If a fixed percentage of deaths in these men with recently diagnosed cancers were misattributed to prostate cancer, then the prostate cancer mortality rates would also have risen. When the incidence of prostate cancer declined in the mid-1990s, then the pool of prevalent cases also decreased, and so the mortality rates would have also fallen. The strongest evidence for a benefit for screening comes from randomized controlled trials of screening, which can minimize selection bias (systematic differences in comparison groups), lead-time bias (zerotime shift), and length-time bias (preferentially detecting slow-growing tumors). Only 1 randomized screening trial has reported positive results, a population-based Canadian study of 46193 men who were randomly assigned to screening vs no screening. The prostate cancer mortality rate in men undergoing screening was significantly lower than that of the control group. However, the results were challenged because the survival benefit became apparent within only 3 years, a very short time for a screening benefit in a slow-growing cancer with a 5 -year lead time. More importantly, the authors ignored the men who were offered screening but refused to participate. When the data were analyzed by intention-toscreen, there were no mortality differences between the 2 groups. Two large randomized screening studies are currently under way, including the American PLCO Trial and the European Randomized Study of Screening for Prostate Cancer. These studies have sufficient power and follow-up duration to determine the efficacy of screening, but results are several years away. Why should we wait for the results of randomized screening trials when screening is the only available option for reducing the mortality and morbidity of prostate cancer? The urologist Willett Whitmore eloquently voiced the underlying dilemma of prostate cancer screening and treatment. He asked, “Is cure possible in those for whom it is necessary, and is cure necessary in those for whom it is possible?” Although the annual mortality rate of prostate cancer is high, the annual incidence rate is considerably higher. The lifetime risk of dying from prostate cancer is estimated to be 3.4% while the lifetime risk of being diagnosed with prostate cancer is nearly 17%. Obviously, most men with prostate canFrom the New Mexico Veterans Affairs Health Care System, Albuquerque. The author has no relevant financial interest in this article.
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 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 | 0.059 | 0.159 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.024 |
| Scholarly communication | 0.007 | 0.013 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.056 | 0.079 |
| Insufficient payload (model declined to judge) | 0.013 | 0.007 |
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".