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Record W90618538 · doi:10.5489/cuaj.12061

Opportunity lost and found: Any easy way to improve outcomes for prostate cancer patients in the postoperative setting?

2012· article· en· W90618538 on OpenAlexaffabout
D.A. Loblaw

Bibliographic record

VenuePubMed · 2012
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineRandomized controlled trialProstatectomyGuidelineRadiation therapyPopulationProstate cancerEvidence-based medicineSystematic reviewMEDLINEGeneral surgeryCancerSurgeryInternal medicineAlternative medicinePathology

Abstract

fetched live from OpenAlex

Evidence-based medicine is a paradigm shift and is a key component in the provision of high-quality care. The highest quality evidence is clinical practice guidelines based on systematic reviews of the randomized controlled trial (RCT) literature. There are many challenges to successfully complete RCTs and it is problematic to synthesize recommendations when the RCTs have conflicting results. However, in the case of the utility of adjuvant postoperative radiotherapy (ART), this is not the case. There are three RCTs showing improvements in local and biochemical control;1–3 the study with the longest follow-up (SWOG 8794) also demonstrates improvements in distant metastatic disease-free survival and overall survival.2 Cancer Care Ontario (CCO) published a systematic review of the literature and clinical practice guideline on the topic showing that all subgroups benefitted in biochemical control and overall survival from ART (and those with seminal vesicle involvement seemed to benefit more not less).4 It is very interesting to see how this evidence is applied in the pragmatic setting. In this issue of CUAJ, Tyldesley and colleagues have published a population-based analysis of postoperative radiotherapy in British Columbia from 2007 to 2009.5 Many interesting facts are reported. Over the 3-year observation period, 9223 patients were identified from the tumour registry and linked to centralized radiotherapy records. Of these patients, initial therapy was radical prostatectomy in 24%. Postoperatively, 47% had one or more high-risk features (positive surgical margin: 36%; extracapsular spread: 22%; seminal vesicle involvement: 4%).5 Of the 47% with one or more high-risk features, 23% with any adverse features were seen by a radiation oncologist within 6 months of surgery. Only 10% of these patients received adjuvant ART (i.e., 2% of patients with any high-risk features). Of equal interest, 40% of those with adverse features who were seen were advised against ART. Why are the rates of referral (23%) and recommendation (60%) and use of ART (2%) so low for these patients? The first argument is a lack of knowledge. The EORTC and SWOG studies were published in 2005 and 2006, respectively (and all were presented in abstract before the observation period). Despite this, we know that evidence takes a while to diffuse into practice, particularly community practice. How long is too long when we have a treatment with a solid evidence base that improves not just biochemical, but distant metastatic disease and overall survival rates? Is there anything we could have done differently to accelerate this knowledge dissemination? The second argument is that the treatment is too toxic. It is easy to attribute really bad side effects (such as severe hemorrhagic cystitis) to all patients who might get radiation. However, when prospectively collected, the data demonstrate that the risk of serious RT toxicity was low. In the Wiegel trial, 1% and 0% of patients had grade 3 bladder and bowel problems.3 This is despite patients receiving 2-dimensional RT; RT has improved greatly in target localization with image-guided techniques and my experience is that modern RT has even fewer side effects. It is true that patients would require at least 30 visits to a cancer centre for consult, planning and treatment and for some patients this is costly and inconvenient. Much progress has been made in shortening the course of primary external radiation from 34 to 49 treatments to a few as 5 treatments;6–8 work from our group and Kruser and colleagues’ has applied these same techniques in the postoperative setting to improve the convenience without increasing the toxicity.9 The final argument is that early salvage postoperative RT is as good as immediate ART. Non-randomized data argue against this.10–12 However, this question (and the question of the optimal duration of adjuvant androgen deprivation therapy) is currently being tested in the intergroup RCT RADICALS which is open in more than 20 centres across Canada. Patients with any high-risk features should be considered for this trial. In short, ART is being underutilized. This is a lost opportunity not only for our patients, but also the health care system. There are now 6 systemic therapies which improve overall survival in the castrate-resistant prostate cancer setting, but none have improved median survival more than 5 months. A course of each treatment costs between $20 000 and $118 000 on top of the $11 000 to $32 000 of hormone therapy. In comparison, a course of ART costs about $4000 and improves median survival by 23 months. At 10 years, it offers more survival benefit than SPCG4 documented for radical prostatectomy over watchful waiting (8% vs. 5%).2,13 We have a tremendous opportunity to make a meaningful difference in the lives of our patients and the healthcare system – we just need to listen to the evidence and act accordingly.

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 imitation

Not 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.

metaresearch head score (Codex)0.033
metaresearch head score (Gemma)0.184
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.033
Threshold uncertainty score0.175

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.184
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0020.002
Science and technology studies0.0030.007
Scholarly communication0.0100.024
Open science0.0030.008
Research integrity0.0090.013
Insufficient payload (model declined to judge)0.0260.004

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.

Opus teacher head0.029
GPT teacher head0.290
Teacher spread0.260 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

Quick stats

Citations0
Published2012
Admission routes2
Has abstractyes

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