Abnormal PSA tests: delays in referral

BACKGROUND: The main benefit of prostate specific antigen (PSA) testing is to help detect prostate cancer at an early, curable stage. Delays between the first abnormal PSA test and biopsy can undermine that benefit, but have not yet been studied. We investigated delays before biopsy together with associated PSA increases as an indicator of disease progression. METHODS: We identified 241 patients with a primary care referral because of an elevated PSA result (>4 ng/mL) and no previous prostate biopsy. Prostate specific antigen results and intervals between PSA testing, specialist clinic referral, appointment and biopsy were stratified by age. RESULTS: Median times between first abnormal PSA, referral, consultation and biopsy were modest but associated with increases in PSA. Extended delays (>20 months) between first abnormal PSA and referral occurred in 25% of younger men. A PSA result less than 10 ng/mL was the best predictor of a delay to refer. DISCUSSION: Rising PSA and possible cancer progression during investigation for prostate cancer suggest that prompt care is advisable.Alan MF Stapleton, Richard L Johns, Tina Kopsaftis, David J Tambly

Delays in radical prostatectomy for prostate cancer and survival outcomes.

A recent publication in your journal, involving 619 Canadian patients undergoing radical prostatectomy (RP), suggests increased delays to time of surgery may be associated with higher rates of biochemical recurrence(BCR)1 in men with high risk disease. However BCR per se is not strongly correlated to the “hard” outcomes of developing metastases or increase cancer mortality which are more heavily influenced by Gleason score (GS) and pathological stage. The manuscript concludes “…further studies are warranted to … assess the impact of SWT (surgical wait time) on cancer-specific survival and overall survival (OS)” and additional retrospective studies with larger cohorts were requested. In the state of South Australia we have the longest running prostate cancer registry in the Southern Hemisphere, and have performed such an analysis in respect of prostate cancer outcomes and delays in care2. We identified 3,140 eligible patients between 1998 and 2013, included all treatment types (RP, radiotherapy [RT], androgen deprivation [ADT]), local and advanced disease and examined the effect of treatment delay (time from diagnosis to date of first treatment) on prostate cancer specific mortality (PCSM) and OS, using Cox Proportional Hazards modelling and competing risks regression, comparing quartiles of delay across the cohort. Adjustment was made for age, PSA levels, treatment modality and GS. Quartiles of delay were as follows (days)—Q1: 35, Q2: 86, Q3: 138.0, Q4: 264. Quartile two was used as the reference point and extensive subgroup analyses were conducted. Shorter delays were associated with hormonal treatment, high Gleason score and high PSA values. PCSM, in an age adjusted model, was highest in Q1 (HR-4.37) compared to Q3 (HR-1.29) and Q4 (HR-1.55). After additional adjustment for GS, PSA value and treatment type, Q1 still remained at highest risk (HR-2.46). The fact shorter delays were associated with poorer outcomes is possibly explained because patients with high PSA levels and high GS at biopsy are more likely to receive treatment sooner, because they represented more aggressive disease. When examining only patients treated with curative intent (RP or RT), delays in Q3 were associated with increased risk of PCSM (HR-2.07), though on sub analysis of RP alone and RT alone, no quartile showed increased risk. On examining the effect of NCCN risk profile, only those in “high risk” group appeared to be at increased risk of poor outcomes, particularly in the context of a short time to treatment. However this most likely reflects the underlying aggressive biology of the disease which led to these patients being treated more quickly in the first place. A similar trend was observed for OS, however after stratification by GS no association between delay and OS could be demonstrated, and within each GS stratum, delays in care were not associated with variation in overall survival. We draw readers’ attention to these findings, which in part, provide the additional evidence from a larger cohort which the authors request

Clinical and socio-demographic profile of an Australian multi-institutional prostate cancer cohort

Aims: To describe the clinical and socio-demographic data from a South Australian prostate cancer cohort (PCCOD). Methods: Clinical data for 2329 prostate cancer patients treated at three South Australian teaching hospitals between 1998 and 2007 were analyzed by place of residence, time of diagnosis and socioeconomic status (SES). χ2 tests were used to investigate differences in stage, grade and prostate-specific antigen (PSA) at diagnosis, among subgroups and over time. Logistic regression was used to examine predictors of treatment modalities. Five-year survival was assessed using Kaplan–Meier methods. Results: The distributions of age, SES and place of residence of PCCOD patients closely reflected those of the state-based prostate cancer population, with rural patients slightly underrepresented. Lower SES or rural residence was not associated with higher stage, grade, PSA level or disease-specific survival. Treatment modalities varied with SES (for radical prostatectomy), rural residence (radical prostatectomy, radiotherapy and androgen ablation), age and clinical characteristics. There was a trend over time towards a younger age at diagnosis and more favorable clinical profiles, consistent with earlier diagnosis. However, the current risk profile for this cohort is similar to that reported approximately a decade earlier in a US series. Conclusion: PCCOD patients have a broadly similar socio-demographic profile to prostate cancer patients statewide. Socioeconomic status is not associated with clinical characteristics at diagnosis, but does predict treatment type. The clinical characteristics of the cohort are consistent with a much later stage presentation than reported in current US case series.Kerri Beckmann, Carole B Pinnock, David J Tamblyn, Tina Kopsaftis, Alan MF Stapleton and David M Rode

Prostate cancer in men aged less than 50 years at diagnosis

Podium Presentation Abstracts No. 48N. Kinnear, G. Kichenadasse, S. Plagakis, M. O, Callaghan, T. Kopsaftis, S. Walsh And D. Forema

Prostate cancer in men aged less than 50 years at diagnosis

Prostate cancer (CaP) in younger men (age ≤50 years) appears to present differently compared with older men. This study describes CaP characteristics and outcomes in Australian young men.The South Australian Prostate Cancer Clinical Outcomes Collaborative database was used to identify men diagnosed with CaP 1998-2012. Men were stratified by age at diagnosis into groups ≤50, 50-70 and ≥70 years. Primary outcomes of cumulative biochemical recurrence (BCR) and cumulative prostate cancer-specific mortality (PCSM) were assessed at 5 and 10 years.In total, 7018 men were included. At time of diagnosis, 182 (2.6 %) were aged ≤50 years. Median follow-up exceeded 4 years. Younger men had a greater proportion of T stage <2 disease, lower median PSA and higher rates of Gleason score <7 (all p < 0.001). They were more likely to experience active surveillance (AS) (4.9, 3.1, 1.5 %) or radical prostatectomy (RP) (70, 55, 8 %) and less likely radiotherapy (13, 24, 29 %) as their principal modality (all p < 0.001). Although only 4.9 % underwent AS, 48 % of men ≤50 years were eligible for AS. Men ≤50 years had both the lowest unadjusted cumulative BCR and PCSM at 10 years. After multivariate analysis, BCR was not significantly different. Sample size limited multivariate analysis of PCSM.In our cohort, men ≤50 years with CaP had less aggressive clinical characteristics, but were more likely to undergo RP. They appear to experience lower unadjusted PCSM, but similar rates of adjusted BCR. Further studies are needed to assess whether AS is appropriately utilised in these men.N. J. Kinnear, G. Kichenadasse, S. Plagakis, M. E. O' Callaghan, T. Kopsaftis, S. Walsh, D. Forema

Prostate-specific antigen (PSA) rate of decline post external beam radiotherapy predicts prostate cancer death

Background and purposeTo assess the association between PSA velocity (PSAV) in the first 24 months after external beam radiotherapy (EBRT) and prostate cancer-specific mortality (PCSM) and all cause mortality.Materials and methodsAll eligible patients in the South Australian (SA) Prostate Cancer Clinical Outcomes registry were followed. 848 Patients treated by definitive EBRT with more than one PSA recorded in the two year post-treatment were included. We calculated PSAV by linear regression.ResultsThe mean number of PSA measurements in the 2year period was 4.4 (SD1.9). The median PSAVs across quartiles (Q1-Q4) were -4.17, -1.29, -0.38 and 0.20ng/ml/yr. In multivariable analysis, a U-shaped relationship was seen between PSAV and PCSM with Q1-Q4 hazard ratios (HR) being 3.82 (1.46-10.00), 3.07 (1.10-8.58), 1, 5.15 (1.99-13.30) respectively. HR for all cause mortality in a similar model were 1.79 (1.07-2.98), 1.55 (0.93-2.59), 1.00 and 1.74 (1.04-2.90) for Q1 to Q4 respectively. A rapid PSA decline in the first year was a strong predictor of PCSM. However, in the second year PSA increase was positively associated with PCSM.ConclusionA rapid decline in PSA in the first year following EBRT is positively associated with PCSM. This may be a useful early indicator of the need for additional therapies.Zumin Shi, Carole B. Pinnock, Stephen Kinsey-Trotman, Martin Borg, Kim L. Moretti, Scott Walsh, Tina Kopsafti

Entrepreneurship and Innovation in Functional Regions

The purpose of this paper is to discuss the role of entrepreneurship and innovations foreconomic development in functional regions and in doing that highlighting the differentconditions offered for entrepreneurship and innovations in functional regions of various sizes.In conclusion, the conditions for entrepreneurship and innovations vary substantially betweenfunctional regions, since the necessary knowledge resources tend to be local and to cluster incertain regions and not others. Functional regions with a high capacity to generate new ideas,create knowledge, organizational learning and innovations are characterized as learningregions. Large functional regions offer a large market potential and a superior accessibility toknowledge and knowledge resources and they will further develop their creative capabilitiesdue to an accumulation of innovative and entrepreneurial knowledge.QC 2012020