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A pilot study of endorectal magnetic resonance imaging and magnetic resonance spectroscopic imaging changes with dutasteride in patients with low risk prostate cancer

2011· article· en· W1569663503 on OpenAlexaff
Hans T. Chung, Susan M. Noworolski, John Kurhanewicz, Vivian Weinberg, Mack Roach

Bibliographic record

VenueBritish Journal of Urology · 2011
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoSunnybrook Health Science Centre
FundersUniversity of California, San FranciscoGlaxoSmithKline
KeywordsDutasterideMedicineProstate cancerMagnetic resonance imagingMagnetic resonance spectroscopic imagingProstateUrologyClinical trialCancerRadiologyInternal medicine

Abstract

fetched live from OpenAlex

Study Type – Therapy (case series) Level of Evidence 4 What’s known on the subject? and What does the study add? While not approved by the Food and Drug Administration (FDA) for chemoprevention, dutasteride has been shown in a large randomized trial to reduce the overall risk of developing prostate cancer. In our pilot study, one third of patients demonstrated a significant reduction in the volume of their prostate cancer as measured by magnetic resonance spectroscopic imaging. OBJECTIVE • To evaluate the effects of dutasteride on treatment‐naïve prostate cancer in men using serial magnetic resonance imaging (MRI) and magnetic resonance spectroscopic imaging (MRSI) in this pilot study. PATIENTS AND METHODS • This investigator‐initiated prospective single‐arm study was approved by the institutional committee on human research ethics board. • The target accrual was 10 patients. Newly diagnosed prostate cancer patients with low risk disease either with symptomatic benign prostatic hypertrophy or deemed to require pre‐brachytherapy androgen suppression therapy were eligible. In the latter group, dutasteride was used to achieve cytoreduction. • All patients received 6 months of dutasteride 3.5 mg daily and underwent baseline blood work, health‐related quality of life indices and MRI/MRSI, which were repeated at 1, 3 and 6 months. • MRSI spectra were examined and scored as healthy or cancerous. The change in cancerous volumes over time was evaluated. RESULTS • Of the 10 patients enrolled, nine patients completed the entire study. One patient withdrew after 3 months because of drug‐related toxicity. • Because a significant decrease in citrate and polyamines on MRSI spectra was noted at 1 month compared with baseline, healthy tissue appeared to be more like cancer and thus created a false impression that the cancer had grown after 1 month. To reduce this bias, comparisons were made between the 1‐month and 6‐month scans. • The median MR cancer volumes at 6 months and 3 months were 100% and 101% of the 1‐month value, respectively. Three of the nine patients had a 30–45% decrease in cancer volume at 6 months relative to 1‐month measures. Of the others, two had no change in cancer volume and four had an increase (range 65–167% of the 1‐month value). • The median cancer volume (range) at baseline was only 0.5 (0.1–5.6) mL. CONCLUSIONS • The inclusion of only men with low volume disease may have limited our ability to accurately assess response rates after dutasteride due to the background effects on normal prostate metabolism. Despite this, one‐third of patients had a 30–45% reduction in cancer volume at 6 months. • Future studies including men with larger volume disease may enable estimates of response rates to be made more accurately.

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)0.003
metaresearch head score (Gemma)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.007
GPT teacher head0.217
Teacher spread0.210 · 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

Citations8
Published2011
Admission routes1
Has abstractyes

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