Real-World Treatment Patterns and Survival Outcomes in Metastatic Hormone-Sensitive Prostate Cancer: Insights From a Retrospective Cohort Study

Despite the predominant use of novel hormonal therapy (NHT), patients in this cohort exhibited aggressive disease and poor survival outcomes. These findings highlight a critical need for more intensive and tailored treatment strategies for mHSPC.

Authors

Institutions

Publication Details

Journal
Cancer Management and Research
Published
2025-03-01
DOI
https://doi.org/10.2147/cmar.s506423
Citations
2
Primary Topic
Prostate Cancer Treatment and Research
Type
article
Field-Weighted Citation Impact
3.04
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Real-World Treatment Patterns and Survival Outcomes in Metastatic Hormone-Sensitive Prostate Cancer: Insights From a Retrospective Cohort Study

Emad Tashkandi
2 citations
Cancer Management and Research
Prostate Cancer Treatment and Research
3.04
article

Real-World Treatment Patterns and Survival Outcomes in Metastatic Hormone-Sensitive Prostate Cancer: Insights From a Retrospective Cohort Study

Emad Tashkandi
article en
2 citations

Abstract

Despite the predominant use of novel hormonal therapy (NHT), patients in this cohort exhibited aggressive disease and poor survival outcomes. These findings highlight a critical need for more intensive and tailored treatment strategies for mHSPC.

Cancer Management and ResearchVol. Volume 17
Umm al-Qura University (SA)
Good health and well-being
Openalex Percentile: Top 11%
Prostate Cancer Treatment and Research
3.04
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.