Evidence map›Paper›PMID 34007014›Full record

ArticleProstate cancer and prostatic diseases2021

Physical activity decreases the risk of cancer reclassification in patients on active surveillance: a multicenter retrospective study.

Aldo Brassetti, Mariaconsiglia Ferriero, Giorgio Napodano, Roberto Sanseverino, Fabio Badenchini, Gabriele Tuderti, Umberto Anceschi, Alfredo Bove, Leonardo Misuraca, Riccardo Mastroianni and 3 more

Abstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in Prostate cancer and prostatic diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Trial
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Review
  11. Article
  12. Review
  13. Round up.Indian journal of urology : IJU : journal of the Urological Society of India
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Aldo BrassettiDepartment of Urology, IRCCS "Regina Elena" National Cancer Institute, Rome, Italy. aldo.brassetti@gmail.com.ORCID http://orcid.org/0000-0001-9643-8979
Mariaconsiglia FerrieroDepartment of Urology, IRCCS "Regina Elena" National Cancer Institute, Rome, Italy.
Giorgio NapodanoDepartment of Urology, "Umberto I" Hospital, Nocera Inferiore, Italy.
Roberto SanseverinoDepartment of Urology, "Umberto I" Hospital, Nocera Inferiore, Italy.
Fabio BadenchiniDepartment of Urology, Istituto Nazionale Tumori di Milano, Milan, Italy.
Gabriele TudertiDepartment of Urology, IRCCS "Regina Elena" National Cancer Institute, Rome, Italy.
Umberto AnceschiDepartment of Urology, IRCCS "Regina Elena" National Cancer Institute, Rome, Italy.
Alfredo BoveDepartment of Urology, IRCCS "Regina Elena" National Cancer Institute, Rome, Italy.
Leonardo MisuracaDepartment of Urology, IRCCS "Regina Elena" National Cancer Institute, Rome, Italy.
Riccardo MastroianniDepartment of Urology, "Sapienza" University of Rome, Rome, Italy.
Flavia ProiettiDepartment of Urology, "Sapienza" University of Rome, Rome, Italy.
Michele GallucciDepartment of Urology, IRCCS "Regina Elena" National Cancer Institute, Rome, Italy.
Giuseppe SimoneDepartment of Urology, IRCCS "Regina Elena" National Cancer Institute, Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPhysical activity (PA) is associated with favorable outcomes in prostate cancer (PCa) patients. We assessed its effect on the risk of PCa reclassification (PCaR) during active surveillance.

methodsAnthropometric, demographic, and clinical data concerning men diagnosed with a low-risk PCa and initially managed with active surveillance at the two participating institutions were retrospectively collected. The Physical Activity Scale for the Elderly (PASE) was used for patients' self-assessment of their daily exercise and their consequent stratification into three groups: sedentary (PASE ≤ 65), moderately active (65 < PASE < 125), active (PASE ≥ 125). Kaplan-Meier model was used to evaluate the predictive role of PA on PCaR, computed at 2, 5, 10 years after diagnosis; differences between lifestyle groups were assessed using the log-rank and uni-/multivariable Cox analyses applied to identify predictors of reclassification.

resultsEighty-five patients were included in the analysis, with a median age of 66 years (IQR: 59-70); 16% were active, 45% were former smokers, and 3 presented with metabolic syndrome (MetS). Prostate-specific antigen (PSA) density was 0.12 (IQR: 0.07-0.15); 34 men showed a PSA doubling time <10 years. The Median PASE score was 86 (IQR: 61.5-115.8): 24 patients were sedentary, 46 moderately active, and 15 active. At a median follow-up of 37 months (IQR: 14-53), 25% of patients experienced PCaR. These were less physically active (PASE score 69.3 vs 87.8; p = 0.056) and presented with significantly smaller prostates (46 ml vs 50.7 ml; p = 0.001) and a higher PSAD (0.14 vs 0.10; p = 0.019). At 2 years, the risk of reclassification was 25 ± 5%, while it was 38 ± 7% at both 5 and 10 years. The risk was significantly different in the three PA groups (Log Rank p = 0.033). PASE score was the only independent predictor of PCaR (HR: 0.987; 95%CI: 0.977-0.998; p = 0.016).

conclusionsPA influences PCa evolution, as increasing levels are associated with a significantly reduced risk of tumor reclassification among patients undergoing active surveillance.

Indexed as

ExerciseWatchful WaitingAgedDisease ProgressionHumansMaleMiddle AgedProstatic NeoplasmsRetrospective StudiesRisk Factors

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.