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Abstract

Background:

Cribriform pattern 4 (CP4) is an aggressive variant in prostate cancer linked to worse clinical outcomes, including biochemical recurrence, metastases, and prostate cancer-specific mortality. However, its prognostic significance across age groups remains unclear. This study investigates whether the impact of CP4 on progression-free survival (PFS) differs by age in patients undergoing radical prostatectomy (RP).

Methods:

This retrospective analysis used patient data from the TCGA database, evaluating patients who underwent RP stratified by CP4 status. The primary outcome was PFS, defined as the time from RP to biochemical recurrence, radiographic progression, or death from any cause. Multivariable Fine-Gray competing risk regression analyses assessed the association between CP4 and PFS, adjusting for preoperative prostate-specific antigen (PSA), Gleason score, tumor stage, and surgical margin status. An interaction term between age (dichotomized at 60 years to facilitate clinical interpretation and applicability, approximating the cohort median age of 61 years [interquartile range = 56-66]) and CP4 status was included in the analysis.

Results:

Of 431 patients, CP4 was present in 134 (31%). In multivariable analysis, CP4 was associated with significantly worse PFS in patients older than 60 years (adjusted hazard ratio [AHR]: 1.99, 95% confidence interval [CI]: 1.01-3.92, P < .001), but not in younger patients (⩽60 years; AHR: 1.00, 95% CI: 0.49-2.04, P = .997). Adjusted 5-year PFS was significantly lower in older CP4-positive patients (50.8%, 95% CI: 33.0%-78.2%) compared with older CP4-negative patients (74.6%, 95% CI: 63.6%-87.6%; P < .001).

Conclusion:

CP4 strongly predicts reduced PFS in patients above 60 years but not younger patients, suggesting that age may influence the clinical impact of CP4. These findings support age-specific risk stratification in CP4-positive prostate cancer. Prospective studies are needed to validate results and explore tailored treatment strategies based on age.

Keywords

Prostatic neoplasms radical prostatectomy cribriform pattern histopathology age factors

Introduction

Prostate cancer (PC) remains a significant global health concern, with treatment decisions heavily influenced by histopathological features. The Gleason grading system serves as the cornerstone of risk stratification, with recent refinements recognizing cribriform pattern 4 (CP4) as an aggressive architectural variant associated with adverse outcomes.¹ Cribriform pattern 4 has been reported in approximately 30% to 40% of PC cases.^2,3 The presence of CP4 has been linked to an increased risk of biochemical recurrence, distant metastasis, and PC-specific mortality, highlighting its prognostic significance.^4-12 However, despite its well-established role as a marker of high-risk disease, the relationship between CP4 and patient age has not been thoroughly investigated.

Advancements in PC imaging have further enhanced diagnostic precision. Multiparametric magnetic resonance imaging (mpMRI) and prostate-specific membrane antigen positron emission tomography/computed tomography are increasingly used in both primary diagnosis and staging, offering improved sensitivity for clinically significant disease compared with conventional imaging.^13-15 These tools play a growing role in refining risk stratification and treatment selection, and may influence the detection and characterization of high-risk pathological features such as CP4.

Age is a critical factor in PC progression and treatment outcomes.^16-18 Older patients often exhibit a different biological response to cancer, potentially driven by immunosenescence, an altered tumor microenvironment, and a distinct molecular profile.^19-22 Furthermore, treatment approaches often differ by age, with younger patients more likely to receive aggressive multimodal therapy, potentially mitigating the adverse effects of CP4. We selected 60 years as the age cutoff because it is commonly used in prior PC studies^23-25 and closely approximates the median age in our cohort, which improves interpretability. Given these considerations, it remains unclear whether the negative impact of CP4 is consistent across different age groups. In this study, we evaluated the age-specific prognostic significance of CP4 in patients undergoing radical prostatectomy (RP). By incorporating multivariable analyses and adjusting for key clinical factors, we aim to clarify the interaction between CP4 and age, providing insights that could refine risk stratification and inform postsurgical treatment decisions.

Materials and Methods

Study population

This retrospective study analyzed individual patient data from those who underwent RP for PC, stratified by the presence or absence of CP4. Inclusion criteria were (1) diagnosis of prostate adenocarcinoma, (2) treatment with RP, and (3) availability of data on age at diagnosis. Patients with missing clinicopathologic or follow-up data relevant to the analysis were excluded. Clinical and pathological variables collected included age at diagnosis, preoperative prostate-specific antigen (PSA) levels, Gleason score, pathological tumor stage, surgical margin status, and nodal involvement. Cribriform pattern 4 status was determined based on pathology review of digitized slides, as described in our prior study.¹² While the review process followed a consistent histopathologic approach, information regarding interobserver reproducibility and blinding was not available, reflecting a limitation of this retrospective analysis. This study was conducted in accordance with the Declaration of Helsinki. The study used publicly available, de-identified data from the TCGA database, therefore it met the exception criteria for Institutional Review Board review at Dana-Farber Cancer Institute, and written informed consent was waived (Decision number: 491519, Date: 02/02/2024). The reporting of this study conforms to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.²⁶ The completed STROBE checklist is provided as Supplementary File 1.

Statistical methods

Comparison of clinical factors stratified by cribriform pattern 4 status

A prespecified statistical analysis plan was followed for this study. Descriptive statistics were used to summarize baseline clinical and pathological characteristics of patients, stratified by the presence or absence of CP4. Categorical variables were compared using the Pearson χ² test or Fisher exact test, as appropriate, while continuous variables were analyzed using the Wilcoxon rank-sum test. The reverse Kaplan-Meier method was employed to estimate the distribution of follow-up times, with differences assessed using the log-rank test.

Covariate-adjusted hazard ratios for progression-free survival

The primary outcome was progression-free survival (PFS), defined as the time from RP to biochemical recurrence, radiographic progression, or death from any cause. Fine-Gray competing risk regression models were used for both univariable and multivariable analyses to evaluate the association between CP4 presence and PFS. The multivariable model included pre-RP PSA level, pathological tumor (pT) stage, Gleason score, and surgical margin status as covariates. In addition, an interaction term for age (⩽60 vs >60 years) was incorporated to improve clinical interpretability, as this cutoff approximates the cohort’s median age (61 years [interquartile range (IQR), 56-66]). Adjusted hazard ratios (AHRs) with 95% confidence intervals (CIs) were reported for each covariate.

Covariate-adjusted estimates of PFS

For the purpose of illustration, covariate-adjusted estimates of PFS were calculated and stratified by CP4 status in patients 60 years or younger and those older than 60 years. These estimates, along with their corresponding 95% CIs, were adjusted for pre-RP PSA level, pathological tumor (pT) stage, Gleason score, and surgical margin status. All statistical analyses were performed using R version 4.2.3 (R Foundation for Statistical Computing, Vienna, Austria), with a 2-sided P value < .05 considered statistically significant. No formal sample size calculation was performed, as this was a retrospective study utilizing all eligible patients from the TCGA database.

Results

Clinical factor distribution by cribriform pattern 4 status

A total of 431 patients who underwent RP for PC were included in this study. Among them, 134 (31%) had CP4, while 297 (69%) did not. Baseline characteristics stratified by CP4 status are summarized in Table 1. Patients with CP4 had significantly higher pre-RP PSA levels compared with those without CP4 (8.4 vs 7.0 ng/mL, P = .006). In addition, a greater proportion of CP4-positive patients had tumors staged pT3a or higher (72% vs 50%, P < .001). There were no statistically significant differences in Gleason score distribution (P = .600), margin status (P = .400), or nodal involvement (P = .061) between the CP4 and non-CP4 groups.

Table 1.

Comparison of the distribution of clinical and treatment factors stratified by the presence of cribriform pattern 4.

	CP4 (n = 134)	Non-CP4 (n = 297)	p
Age (years), median (IQR)	62 (57, 66)	61 (56, 66)	0.344
Baseline PSA, ng/ml, median (IQR)	8.4 (5.2, 14.0)	7.0 (5.0, 9.7)	0.006
Prostatectomy tumor stage, No. (%)			< 0.001
T2	37 (28%)	148 (50%)
T3a or higher	97 (72%)	146 (50%)
Prostatectomy Gleason score, No. (%)			0.600
8	29 (41%)	29 (37%)
9-10	41 (59%)	50 (63%)
Prostatectomy margin status, No. (%)			0.400
Negative	90 (68%)	209 (72%)
Positive	43 (32%)	82 (28%)
Prostatectomy nodal status, No. (%)			0.061
Negative (N0)	103 (79%)	220 (87%)
Positive (N1)	27 (21%)	34 (13%)
Follow-up (month), median (IQR)^a	52.53 (22.67, 70.23)	40.73 (25.63, 80.10)	0.352

Abbreviations: CP4, cribriform pattern 4; non-CP4, non-cribriform pattern 4; PSA, prostate-specific antigen; IQR, interquartile range.

Reverse KM method is used to estimate time of median follow-up.

Covariate-adjusted hazard ratios for PFS

Over a median follow-up period of 32.6 months (IQR: 20.4-53.1), 82 (19.03%) patients had biochemical recurrence, 6 (1.39%) patients had locoregional recurrence, 2 (0.46%) patients had distant metastasis, and 8 (1.85%) patients died. As shown in Table 2, CP4 was associated with a significantly lower PFS in patients older than 60 years (AHR: 1.99, 95% CI: 1.01-3.92, P < .001), whereas it did not significantly impact PFS in those 60 years or younger (AHR: 1.00, 95% CI: 0.49-2.04, P = .997).

Table 2.

Covariate-adjusted hazard ratios for progression-free survival.

Covariates	No. of men	No. of events	Multivariable
Covariates	No. of men	No. of events	AHR	95% CI	p
Baseline PSA, ng/ml
< 4	42	7	0.675	0.2727 – 1.672	0.395
4-10	261	56	Reference	Reference
> 10	124	33	0.875	0.519 – 1.474	0.615
Prostatectomy tumor stage
T2	185	34	Reference	Reference
T3a or higher	243	64	1.128	0.677 – 1.879	0.642
Prostatectomy margin status
Negative	299	65	Reference	Reference
Positive	125	33	0.819	0.467 – 1.437	0.487
Prostatectomy Gleason score
8	58	9	Reference	Reference
9-10	91	40	2.697	1.550 – 4.693	< 0.001
CP4 in men 60 years or younger
No	137	26	Reference	Reference
Yes	61	20	1.001	0.490 – 2.044	0.997
CP4 in men older than 60 years
No	160	31	Reference	Reference
Yes	73	21	1.994	1.013 – 3.924	< 0.001

Abbreviations: CP4, cribriform pattern 4; non-CP4, non-cribriform pattern 4; PSA, prostate-specific antigen; AHR, adjusted hazard ratios; CI, confidence interval.

Covariate-adjusted estimates of PFS

Figure 1 illustrates the covariate-adjusted PFS estimates stratified by CP4 status in different age groups. In patients older than 60 years, those with CP4 had a significantly lower adjusted 5-year PFS (50.8%, 95% CI: 33.0%-78.2%) compared with those without CP4 (74.6%, 95% CI: 63.6%-87.6%) (P < .001). In contrast, in patients 60 years or younger, the adjusted 5-year PFS was 91.8% (95% CI: 82.6%-99.6%) in the non-CP4 group and 90.7% (95% CI: 81.9%-100%) in the CP4 group (P = .063), indicating no significant difference.

Figure 1.

Covariate-adjusted estimates of progression-free survival (A) older than age 60 years and (B) 60 years or younger stratified by the presence of cribriform pattern 4.

Discussion

In this study, we investigated the age-specific prognostic significance of CP4 in PC following RP. Our findings demonstrate that CP4 is an independent predictor of PFS in patients older than 60 years, whereas its presence did not significantly impact PFS in patients 60 years or younger. These results suggest that age may modify the clinical relevance of CP4, potentially influencing risk stratification and post-surgical treatment decisions. These findings build upon our prior studies using the same TCGA cohort, in which we previously demonstrated that CP4 is associated with worse PFS and distinct genomic alterations in PC overall,¹² as well as in patients with Gleason score 8-10 disease specifically.²⁷ In contrast, the current study addresses whether the prognostic impact of CP4 is modified by patient age—an aspect that had not been previously explored.

Cribriform pattern 4 has consistently been associated with aggressive tumor biology, including higher rates of biochemical recurrence, distant metastases, and PC-specific mortality.^4-12 Prior studies have established CP4 as a high-risk feature independent of Gleason score. However, the interaction between CP4 and patient age has not been well characterized. Our study is the first to demonstrate that CP4’s prognostic impact varies by age, with a significant effect observed only in men older than 60 years. Several biological mechanisms may underlie this age-specific disparity. Older patients experience immunosenescence, leading to reduced immune surveillance and impaired ability to control tumor progression.^28,29 In addition, the tumor microenvironment evolves with age, with increased fibrosis and alterations in stromal signaling that may facilitate CP4-driven tumor aggression in older patients.^22,30,31 The higher genomic instability observed in CP4-positive tumors may be more detrimental in an older host with reduced capacity for genomic repair.^32,33 In contrast, younger patients may better tolerate CP4-associated tumor aggression, possibly due to a more resilient immune response^34,35 or a greater likelihood of receiving timely salvage therapy after biochemical recurrence.³⁶

Our findings expand upon previous studies that identified CP4 as an independent predictor of poor outcomes across various Gleason grade groups. Notably, our results indicate that CP4 may not confer the same level of risk in younger patients, highlighting the potential for age-specific risk stratification. From a clinical management perspective, these findings suggest that older patients with CP4-positive tumors may benefit from closer post-RP surveillance and earlier consideration of adjuvant therapy, such as radiotherapy and androgen deprivation therapy. This hypothesis warrants further validation in prospective clinical trials.

This study has several limitations. First, its retrospective nature introduces inherent selection biases, and while we adjusted for key clinical covariates, residual confounding cannot be excluded. In addition, the TCGA RP cohort may not fully reflect real-world surgical populations, as cases selected for TCGA were often enriched for higher-grade or genomically informative tumors. Moreover, variations in patient ethnicity, surgical technique, and institutional practices within the TCGA cohort may further limit the external validity of our findings. This selection bias may limit the generalizability of our findings. Second, data on post-RP adjuvant or salvage therapies were not available, which may have influenced PFS outcomes, particularly in younger patients who are more likely to receive earlier or more aggressive salvage treatment following biochemical recurrence. This could attenuate the apparent prognostic impact of CP4 in this subgroup and confound age-specific differences in PFS.^37,38 In addition, older patients have a higher risk of death from non-PC causes, which may act as a competing risk and influence the Fine-Gray model estimates. While competing risk methods were used, differences in baseline comorbidity or life expectancy between age groups may still confound the interpretation of CP4’s prognostic impact. Moreover, our analysis relied on chronological age, which may not fully capture biologic variability among patients; incorporating measures of biological age or comorbidity burden in future studies could provide a more refined understanding of CP4’s prognostic relevance. Third, the median follow-up period in the TCGA cohort is relatively short, and PC recurrences can occur many years after surgery. As a result, the study may underestimate the long-term prognostic implications of CP4, particularly in younger patients with longer life expectancy. Forth, while we identified an age threshold of 60 years, the optimal cutoff remains uncertain. This cutoff was selected a priori to improve clinical interpretability, as it closely approximates the cohort’s median age. However, due to the limited sample size, sensitivity analyses were not performed, and future studies with larger cohorts may help refine this classification. Finally, as no priori sample size calculation was performed, the study may be underpowered to detect smaller effect sizes, particularly in subgroup analyses. Despite these limitations, our findings provide novel insights into the prognostic role of CP4 and its age-specific effects on PFS.

Conclusion

This study highlights the differential impact of CP4 on PFS based on patient age, demonstrating that CP4 is a strong predictor of worse outcomes in men older than 60 years but not in younger patients. These findings suggest that age should be considered when stratifying CP4-positive PC patients for post-RP treatment decisions. Future research should focus on validating these results in prospective cohorts and evaluating the role of age-adapted treatment strategies for CP4-positive disease.

Supplemental Material

sj-docx-1-onc-10.1177_11795549251363324 – Supplemental material for Age-Specific Impact of Cribriform Pattern in Prostate Cancer Following Radical Prostatectomy

Supplemental material, sj-docx-1-onc-10.1177_11795549251363324 for Age-Specific Impact of Cribriform Pattern in Prostate Cancer Following Radical Prostatectomy by Ari S Hilibrand, Yetkin Tuac, Okan Argun, Christina M. Breneman, Michelle Oh, Shalini Moningi, Jonathan E Leeman and Mutlay Sayan in Clinical Medicine Insights: Oncology

Footnotes

Acknowledgements

We gratefully acknowledge the patients whose data were made available through the Cancer Genome Atlas and the researchers who generated this invaluable resource.

ORCID iDs

Christina M. Breneman

Mutlay Sayan

Ethical Considerations

The study was conducted according to the guidelines of the Declaration of Helsinki, and met the exception criteria for the Institutional Review Board review at Dana-Farber Cancer Institute (Exception Code: 491519, Date: 02/02/2024).

Consent to Participate

Not applicable

Consent for Publication

Not applicable

Author Contributions

Conceptualization, ASH and MS; Methodology, ASH, YT, and MS, Writing—Original Draft Preparation, ASH., YT, and MS; Writing—Review & Editing, ASH, YT, OA, CMB, MO, SM, JEL, and MS; Supervision, MS. All authors have read and agreed to the published version of the manuscript.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding author.

Supplemental Material

Supplemental material for this article is available online.

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Supplementary Material

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