James G. Kench
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Recognitions
James G. Kench has a total of 1000 co-authors. Here are the top co-authors by number of shared publications:
- Lisa G. Horvath
Chris O'Brien Lifehouse, Sydney, Australia
93 shared publications - Phillip D. Stricker
Garvan Institute of Medical Research 4 , Sydney, Australia
62 shared publications - Anthony Michael Joshua
Kinghorn Cancer Centre, St Vincent's Hospital Sydney Australia
58 shared publications - Luke A. Selth
Flinders University, College of Medicine and Public Health, Flinders Health and Medical Research Institute, Bedford Park, SA, 5042, Australia.
48 shared publications - Alexander Swarbrick
Cancer Ecosystems Program, Garvan Institute of Medical Research, Darlinghurst, Australia
40 shared publications - Daniel Lee Roden
Garvan Institute of Medical Research 1 Cancer Ecosystems Program Darlinghurst, Australia
40 shared publications
Latest Publications
- Open Access
- 15 October 2026
- Published by American Association for Cancer Research (AACR)
Data from AI-Based Pathology Classifier Predicts Sensitivity to Enzalutamide in Metastatic Hormone-Sensitive Prostate Cancer: A Biomarker Analysis of the ENZAMET Trial
Purpose:The ENZAMET trial established that enzalutamide added to androgen deprivation therapy (ADT) improves overall survival (OS) in metastatic hormone-sensitive prostate cancer (mHSPC), but treatment response is heterogeneous. We tested whether the artificial intelligence pathology image classifier (APIC), previously developed and locked in CHAARTED, predicts OS benefit from enzalutamide in ENZAMET. Experimental Design:This biomarker study applied APIC to digitized hematoxylin and eosin specimens from ENZAMET [Australian and New Zealand Urogenital and Prostate Cancer Trials Group (ANZUP) 1304, NCT02446405]. ENZAMET randomized participants with mHSPC to ADT plus enzalutamide or nonsteroidal antiandrogen (NSAA), with early concurrent docetaxel permitted. APIC was applied without modification or retraining. The prespecified primary analysis evaluated the treatment-by-APIC interaction for OS using Cox models adjusted for standard clinical factors. Prespecified sensitivity analysis excluded participants receiving early concurrent docetaxel. Results:Among 1,125 participants, 492 with digitized tissue (median follow-up, 68.8 months) were eligible. APIC classified 316 (64%) as APIC negative and 176 (36%) as APIC positive. APIC significantly modified enzalutamide benefit (interaction P = 0.014). APIC-negative disease showed improved survival with enzalutamide versus NSAA [HR, 0.50; 95% confidence interval (CI), 0.35–0.73; 60-month OS, 76.5% vs. 58.3%], whereas APIC-positive disease showed limited evidence of benefit (HR, 1.04; 95% CI, 0.67–1.62; 60-month OS, 55.6% vs. 58.8%). In low-volume disease, enzalutamide improved survival in APIC-negative (HR, 0.31; 95% CI, 0.16–0.62) but not APIC-positive disease (HR, 1.04; 95% CI, 0.53–2.06; interaction P = 0.015). For non–docetaxel-treated participants, enzalutamide benefit was greater in APIC-negative (HR, 0.40; 60-month OS 82% vs. 61.0%) than in APIC-positive participants (HR, 0.79; 60-month OS, 62.8% vs. 57.6%). Conclusions:The presence of APIC-negative disease identified participants with a major improvement in OS with the addition of enzalutamide to ADT compared with the addition of NSAA.
- 15 October 2026
- Published by American Association for Cancer Research (AACR)
Open AccessData from AI-Based Pathology Classifier Predicts Sensitivity to Enzalutamide in Metastatic Hormone-Sensitive Prostate Cancer: A Biomarker Analysis of the ENZAMET Trial
Purpose:The ENZAMET trial established that enzalutamide added to androgen deprivation therapy (ADT) improves overall survival (OS) in metastatic hormone-sensitive prostate cancer (mHSPC), but treatment response is heterogeneous. We tested whether the artificial intelligence pathology image classifier (APIC), previously developed and locked in CHAARTED, predicts OS benefit from enzalutamide in ENZAMET. Experimental Design:This biomarker study applied APIC to digitized hematoxylin and eosin specimens from ENZAMET [Australian and New Zealand Urogenital and Prostate Cancer Trials Group (ANZUP) 1304, NCT02446405]. ENZAMET randomized participants with mHSPC to ADT plus enzalutamide or nonsteroidal antiandrogen (NSAA), with early concurrent docetaxel permitted. APIC was applied without modification or retraining. The prespecified primary analysis evaluated the treatment-by-APIC interaction for OS using Cox models adjusted for standard clinical factors. Prespecified sensitivity analysis excluded participants receiving early concurrent docetaxel. Results:Among 1,125 participants, 492 with digitized tissue (median follow-up, 68.8 months) were eligible. APIC classified 316 (64%) as APIC negative and 176 (36%) as APIC positive. APIC significantly modified enzalutamide benefit (interaction P = 0.014). APIC-negative disease showed improved survival with enzalutamide versus NSAA [HR, 0.50; 95% confidence interval (CI), 0.35–0.73; 60-month OS, 76.5% vs. 58.3%], whereas APIC-positive disease showed limited evidence of benefit (HR, 1.04; 95% CI, 0.67–1.62; 60-month OS, 55.6% vs. 58.8%). In low-volume disease, enzalutamide improved survival in APIC-negative (HR, 0.31; 95% CI, 0.16–0.62) but not APIC-positive disease (HR, 1.04; 95% CI, 0.53–2.06; interaction P = 0.015). For non–docetaxel-treated participants, enzalutamide benefit was greater in APIC-negative (HR, 0.40; 60-month OS 82% vs. 61.0%) than in APIC-positive participants (HR, 0.79; 60-month OS, 62.8% vs. 57.6%). Conclusions:The presence of APIC-negative disease identified participants with a major improvement in OS with the addition of enzalutamide to ADT compared with the addition of NSAA.
- Open Access
- 15 October 2026
- Published by American Association for Cancer Research (AACR)
Supplementary Figure S10 from AI-Based Pathology Classifier Predicts Sensitivity to Enzalutamide in Metastatic Hormone-Sensitive Prostate Cancer: A Biomarker Analysis of the ENZAMET Trial
Adverse event rates by APIC status in patients receiving enzalutamide versus NSAA
- 15 October 2026
- Published by American Association for Cancer Research (AACR)
Open AccessSupplementary Figure S10 from AI-Based Pathology Classifier Predicts Sensitivity to Enzalutamide in Metastatic Hormone-Sensitive Prostate Cancer: A Biomarker Analysis of the ENZAMET Trial
Adverse event rates by APIC status in patients receiving enzalutamide versus NSAA
- Open Access
- 15 October 2026
- Published by American Association for Cancer Research (AACR)
Supplementary Figure S2 from AI-Based Pathology Classifier Predicts Sensitivity to Enzalutamide in Metastatic Hormone-Sensitive Prostate Cancer: A Biomarker Analysis of the ENZAMET Trial
Clinical progression-free survival by treatment arm and APIC status
- 15 October 2026
- Published by American Association for Cancer Research (AACR)
Open AccessSupplementary Figure S2 from AI-Based Pathology Classifier Predicts Sensitivity to Enzalutamide in Metastatic Hormone-Sensitive Prostate Cancer: A Biomarker Analysis of the ENZAMET Trial
Clinical progression-free survival by treatment arm and APIC status
- Open Access
- 15 October 2026
- Published by American Association for Cancer Research (AACR)
Supplementary Figure S3 from AI-Based Pathology Classifier Predicts Sensitivity to Enzalutamide in Metastatic Hormone-Sensitive Prostate Cancer: A Biomarker Analysis of the ENZAMET Trial
PSA progression-free survival by treatment arm and APIC status
- 15 October 2026
- Published by American Association for Cancer Research (AACR)
Open AccessSupplementary Figure S3 from AI-Based Pathology Classifier Predicts Sensitivity to Enzalutamide in Metastatic Hormone-Sensitive Prostate Cancer: A Biomarker Analysis of the ENZAMET Trial
PSA progression-free survival by treatment arm and APIC status
- Open Access
- 15 October 2026
- Published by American Association for Cancer Research (AACR)
Supplementary Figure S1 from AI-Based Pathology Classifier Predicts Sensitivity to Enzalutamide in Metastatic Hormone-Sensitive Prostate Cancer: A Biomarker Analysis of the ENZAMET Trial
Overall survival by treatment arm and APIC status
- 15 October 2026
- Published by American Association for Cancer Research (AACR)
Open AccessSupplementary Figure S1 from AI-Based Pathology Classifier Predicts Sensitivity to Enzalutamide in Metastatic Hormone-Sensitive Prostate Cancer: A Biomarker Analysis of the ENZAMET Trial
Overall survival by treatment arm and APIC status
- Open Access
- 15 October 2026
- Published by American Association for Cancer Research (AACR)
Supplementary Figure S4 from AI-Based Pathology Classifier Predicts Sensitivity to Enzalutamide in Metastatic Hormone-Sensitive Prostate Cancer: A Biomarker Analysis of the ENZAMET Trial
Multivariable Cox regression analysis of overall survival
- 15 October 2026
- Published by American Association for Cancer Research (AACR)
Open AccessSupplementary Figure S4 from AI-Based Pathology Classifier Predicts Sensitivity to Enzalutamide in Metastatic Hormone-Sensitive Prostate Cancer: A Biomarker Analysis of the ENZAMET Trial
Multivariable Cox regression analysis of overall survival
- Open Access
- 15 October 2026
- Published by American Association for Cancer Research (AACR)
Supplementary Figure S5 from AI-Based Pathology Classifier Predicts Sensitivity to Enzalutamide in Metastatic Hormone-Sensitive Prostate Cancer: A Biomarker Analysis of the ENZAMET Trial
Distribution of baseline serum PSA by APIC status
- 15 October 2026
- Published by American Association for Cancer Research (AACR)
Open AccessSupplementary Figure S5 from AI-Based Pathology Classifier Predicts Sensitivity to Enzalutamide in Metastatic Hormone-Sensitive Prostate Cancer: A Biomarker Analysis of the ENZAMET Trial
Distribution of baseline serum PSA by APIC status
- Open Access
- 15 October 2026
- Published by American Association for Cancer Research (AACR)
Supplementary Figure S6 from AI-Based Pathology Classifier Predicts Sensitivity to Enzalutamide in Metastatic Hormone-Sensitive Prostate Cancer: A Biomarker Analysis of the ENZAMET Trial
APIC and specimen type: score distribution and treatment outcomes within each specimen subgroup
- 15 October 2026
- Published by American Association for Cancer Research (AACR)
Open AccessSupplementary Figure S6 from AI-Based Pathology Classifier Predicts Sensitivity to Enzalutamide in Metastatic Hormone-Sensitive Prostate Cancer: A Biomarker Analysis of the ENZAMET Trial
APIC and specimen type: score distribution and treatment outcomes within each specimen subgroup
- Open Access
- 15 October 2026
- Published by American Association for Cancer Research (AACR)
Supplementary Figure S7 from AI-Based Pathology Classifier Predicts Sensitivity to Enzalutamide in Metastatic Hormone-Sensitive Prostate Cancer: A Biomarker Analysis of the ENZAMET Trial
Kaplan-Meier curves showing overall survival by APIC status within the enzalutamide and NSAA arms, stratified by early docetaxel use
- 15 October 2026
- Published by American Association for Cancer Research (AACR)
Open AccessSupplementary Figure S7 from AI-Based Pathology Classifier Predicts Sensitivity to Enzalutamide in Metastatic Hormone-Sensitive Prostate Cancer: A Biomarker Analysis of the ENZAMET Trial
Kaplan-Meier curves showing overall survival by APIC status within the enzalutamide and NSAA arms, stratified by early docetaxel use
- Open Access
- 15 October 2026
- Published by American Association for Cancer Research (AACR)
Supplementary Figure S9 from AI-Based Pathology Classifier Predicts Sensitivity to Enzalutamide in Metastatic Hormone-Sensitive Prostate Cancer: A Biomarker Analysis of the ENZAMET Trial
Baseline cytokine fold differences by APIC status for different subgroups
- 15 October 2026
- Published by American Association for Cancer Research (AACR)
Open AccessSupplementary Figure S9 from AI-Based Pathology Classifier Predicts Sensitivity to Enzalutamide in Metastatic Hormone-Sensitive Prostate Cancer: A Biomarker Analysis of the ENZAMET Trial
Baseline cytokine fold differences by APIC status for different subgroups