A dynamic model for the risk of bladder cancer progression

Multi-state relative survival modelling of colorectal cancer progression and mortality

Accurate identification of factors associated with progression of colorectal cancer remains a challenge. In particular, it is unclear which statistical methods are most suitable to separate the effects of putative prognostic factors on cancer progression vs cancer-specific and other cause mortality. To address these challenges, we analyzed 10 year follow-up data for patients who underwent curative surgery for colorectal cancer in 1985-2000. Separate analyses were performed in two French cancer registries. Results of three multivariable models were compared: Cox model with recurrence as a time-dependent variable, and two multi-state models, which separated prognostic factor effects on recurrence vs death, with or without recurrence. Conventional multi-state model analyzed all-cause mortality while new relative survival multi-state model focused on cancer-specific mortality. Among the 2517 and 2677 patients in the two registries, about 50% died without a recurrence, and 28% had a recurrence, of whom almost 90% died. In both multi-state models men had significantly increased risk of cancer recurrence in both registries (HR=0.79; 95% CI: 0.68-0.92 and HR=0.83; 95% CI: 0.71-0.96). However, the two multi-state models identified different prognostic factors for mortality without recurrence. In contrast to the conventional model, in the relative survival analyses gender had no independent association with cancer-specific mortality whereas patients diagnosed with stage III cancer had significantly higher risks in both registries (HR=1.67; 95% CI: 1.27-2.22 and HR=2.38; 95% CI: 1.29-3.27). In conclusion, relative survival multi-state model revealed that different factors may be associated with cancer recurrence vs cancer-specific mortality either after or without a recurrence.

Depressive symptoms and short telomere length are associated with increased mortality in bladder cancer patients

BACKGROUND

Depression is associated with an increased risk of mortality in patients with cancer; it has been hypothesized that depression-associated alterations in cell aging mechanisms, in particular, the telomere/telomerase maintenance system, may underlie this increased risk. We evaluated the association of depressive symptoms and telomere length to mortality and recurrence/progression in 464 patients with bladder cancer.

METHODS

We used the Center for Epidemiologic Studies Depression Scale (CES-D) and Structured Clinical Interview for DSM-IV Disorder (SCID) to assess current depressive symptoms and lifetime major depressive disorder (MDD), respectively, and telomere length was assessed from peripheral blood lymphocytes. Multivariate Cox regression was used to assess the association of depression and telomere length to outcomes and the joint effect of both. Kaplan-Meier plots and log-rank tests were used to compare survival time of subgroups by depression variables and telomere length.

RESULTS

Patients with depressive symptoms (CES-D ≥ 16) had a 1.83-fold [95% confidence interval (CI), 1.08-3.08; P = 0.024] increased risk of mortality compared with patients without depressive symptoms (CES-D < 16) and shorter disease-free survival time (P = 0.004). Patients with both depressive symptoms and lifetime history of MDD were at 4.88-fold (95% CI, 1.40-16.99; P = 0.013) increased risk compared with patients with neither condition. Compared to patients without depressive symptoms and long telomere length, patients with depressive symptoms and short telomeres exhibited a 4-fold increased risk of mortality (HR, 3.96; 95% CI, 1.86-8.41; P = 0.0003) and significantly shorter disease-free survival time (P < 0.001).

CONCLUSION

Short telomere length and depressive symptoms are associated with bladder cancer mortality individually and jointly.

IMPACT

Further investigation of interventions that impact depression and telomere length may be warranted in patients with cancer.

Risk prediction scores for recurrence and progression of non-muscle invasive bladder cancer: an international validation in primary tumours

Objective

We aimed to determine the validity of two risk scores for patients with non-muscle invasive bladder cancer in different European settings, in patients with primary tumours.

Methods

We included 1,892 patients with primary stage Ta or T1 non-muscle invasive bladder cancer who underwent a transurethral resection in Spain (n = 973), the Netherlands (n = 639), or Denmark (n = 280). We evaluated recurrence-free survival and progression-free survival according to the European Organisation for Research and Treatment of Cancer (EORTC) and the Spanish Urological Club for Oncological Treatment (CUETO) risk scores for each patient and used the concordance index (c-index) to indicate discriminative ability.

Results

The 3 cohorts were comparable according to age and sex, but patients from Denmark had a larger proportion of patients with the high stage and grade at diagnosis (p<0.01). At least one recurrence occurred in 839 (44%) patients and 258 (14%) patients had a progression during a median follow-up of 74 months. Patients from Denmark had the highest 10-year recurrence and progression rates (75% and 24%, respectively), whereas patients from Spain had the lowest rates (34% and 10%, respectively). The EORTC and CUETO risk scores both predicted progression better than recurrence with c-indices ranging from 0.72 to 0.82 while for recurrence, those ranged from 0.55 to 0.61.

Conclusion

The EORTC and CUETO risk scores can reasonably predict progression, while prediction of recurrence is more difficult. New prognostic markers are needed to better predict recurrence of tumours in primary non-muscle invasive bladder cancer patients.

Bayesian analysis of a disability model for lung cancer survival

Bayesian reasoning, survival analysis and multi-state models are used to assess survival times for Stage IV non-small-cell lung cancer patients and the evolution of the disease over time. Bayesian estimation is done using minimum informative priors for the Weibull regression survival model, leading to an automatic inferential procedure. Markov chain Monte Carlo methods have been used for approximating posterior distributions and the Bayesian information criterion has been considered for covariate selection. In particular, the posterior distribution of the transition probabilities, resulting from the multi-state model, constitutes a very interesting tool which could be useful to help oncologists and patients make efficient and effective decisions.