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Related Concept Videos

Generation of Prostate Cancer Patient Derived Xenograft Models from Circulating Tumor Cells08:03

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Three-dimensional cultures of patient BMPC specimens and xenografts of bone metastatic prostate cancer maintain the functional heterogeneity of their original tumors resulting in cysts, spheroids and complex, tumor-like organoids. This manuscript provides an optimization strategy and protocol for 3D culture of heterogeneous patient derived samples and their analysis using...
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The isolation of cancer stem cells (CSCs) directly from human tissues is requisite for their biological characterization. This manuscript describes a methodology for the isolation of prostate CSCs from human tissues, while also providing tips on troubleshooting difficult...
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Related Experiment Video

Updated: Jan 20, 2026

Generation of Prostate Cancer Patient Derived Xenograft Models from Circulating Tumor Cells
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Prostate cancer survival estimates: An application with piecewise hazard function derivation.

Atanu Bhattacharjee1, Atul Budukh1, Rajesh Dikshit1

  • 1Centre for Cancer Epidemiology, The Advanced Centre for Treatment, Research and Education in Cancer, Tata Memorial Centre, Navi Mumbai, Maharastra, India.

South Asian Journal of Cancer
|September 7, 2019
PubMed
Summary

This study introduces a data-driven method for estimating time-dependent hazard functions using piecewise hazard rates. The findings reveal age-related differences in prostate cancer hazard rates, aiding survival trend analysis.

Keywords:
Piecewise hazard functionSEERprostate cancer

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Area of Science:

  • Biostatistics
  • Survival Analysis
  • Epidemiology

Background:

  • Time-dependent hazard functions are crucial for survival analysis but often overlooked.
  • Estimating hazard functions over time presents challenges, necessitating novel methodologies.
  • This research addresses the need for a data-driven approach to estimate hazard functions at various time points.

Purpose of the Study:

  • To propose and validate a novel data-driven method for estimating piecewise hazard rates.
  • To analyze survival trends in prostate cancer patients using time-dependent hazard functions.
  • To provide statistical inference for improved understanding of survival benefits.

Main Methods:

  • A piecewise hazard rate model was formulated and applied to a large cohort of prostate cancer patients (n=610,814).
  • Data from the Surveillance, Epidemiology, and End Results Program (SEER) was utilized for patients aged 40-80+.
  • Follow-up durations were segmented into intervals to estimate piecewise hazard rates, compared using Wald-type tests with an R function.

Main Results:

  • Piecewise hazard rates remained relatively consistent across follow-up intervals, with variations in later stages.
  • Younger prostate cancer patients exhibited lower hazard rates compared to older patients.
  • Hazard rates were analyzed separately for different prostate cancer grades.

Conclusions:

  • The piecewise hazard rate method enhances statistical inference for survival data.
  • This approach offers a deeper understanding of treatment efficacy for prolonged survival across different age groups.
  • The findings underscore the importance of age-specific and grade-specific survival analyses in prostate cancer care.