Evidence map›Paper›PMID 34644741›Full record

ArticleRevista do Colegio Brasileiro de Cirurgioes2021

PSA density of the lesion: a mathematical formula that uses clinical and pathological data to predict biochemical recurrence in prostate cancer patients.

Pedro Henrique Rezende Junqueira, Gabriel Arantes Dos Santos, Marcelo Xavier, Poliana Romão, Sabrina Reis, Miguel Srougi, Willian Carlos Nahas, Carlo Carmargo Passerotti

Open access · goldAbstract read
In one paragraph

Article in Revista do Colegio Brasileiro de Cirurgioes, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 79% of its field
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

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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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

8 authors at 3 institutions in 1 country.

Pedro Henrique Rezende Junqueira- Hospital Oswaldo Cruz, Centro de Cirurgia Robótica - São Paulo - SP - Brasil.
Gabriel Arantes Dos Santos- Faculdade de Medicina da Universidade de São Paulo, Urologia, Laboratório de Investigação Médica - São Paulo - SP - Brasil.ORCID http://orcid.org/0000-0003-1602-9193
Marcelo Xavier- Hospital Oswaldo Cruz, Centro de Cirurgia Robótica - São Paulo - SP - Brasil.
Poliana Romão- Faculdade de Medicina da Universidade de São Paulo, Urologia, Laboratório de Investigação Médica - São Paulo - SP - Brasil.
Sabrina Reis- Faculdade de Medicina da Universidade de São Paulo, Urologia, Laboratório de Investigação Médica - São Paulo - SP - Brasil.
Miguel Srougi- Faculdade de Medicina da Universidade de São Paulo, Urologia, Laboratório de Investigação Médica - São Paulo - SP - Brasil.
Willian Carlos Nahas- Instituto do Câncer de São Paulo, Urologia - São Paulo - SP - Brasil.
Carlo Carmargo Passerotti- Hospital Oswaldo Cruz, Centro de Cirurgia Robótica - São Paulo - SP - Brasil.
Universidade de São Paulo · BRHospital Universitário Oswaldo Cruz · BRInstituto do Câncer do Estado de São Paulo · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A main challenge in the clinical management of prostate cancer is to identify which tumor is aggressive and needs invasive treatment. Thus, being able to predict which cancer will progress to biochemical recurrence is a great strategy to stratify prostate cancer patients. With that in mind, we created a mathematical formula that takes into account the patients clinical and pathological data resulting in a quantitative variable, called PSA density of the lesion, which has the potential to predict biochemical recurrence. To test if our variable is able to predict biochemical recurrence, we use a cohort of 219 prostate cancer patients, associating our new variable and classic parameters of prostate cancer with biochemical recurrence. Total PSA, lesion weight, volume and classic PSA density were positively associated with biochemical recurrence (p<0.05). ISUP score was also associated with biochemical recurrence in both biopsy and surgical specimen (p<0.001). The increase of PSA density of the lesion was significantly associated with the biochemical recurrence (p=0.03). Variables derived from the formula, PSA 15% and PSA 152, were also positive associated with the biochemical recurrence (p=0.01 and p=0.002 respectively). Logistic regression analysis shows that classic PSA density, PSA density of the lesion and total PSA, together, can explain up to 13% of cases of biochemical recurrence. PSA density of the lesion alone would have the ability to explain up to 7% of cases of biochemical recurrence. In conclusion, this new mathematical approach could be a useful tool to predict disease recurrence in prostate cancer.

Indexed as

Prostate-Specific AntigenProstatic NeoplasmsBiopsyHumansMaleNeoplasm Recurrence, LocalProstatectomyProstate-Specific Antigen

Identifiers

PMID34644741
PMCPMC10683463
OpenAlexW3206871676

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