Exploring Determinants of Interdisciplinary Collaboration within a Geriatric Oncology Setting: A Mixed-Method Study

Aims: Lung cancer is the leading cause of cancer death worldwide, and tobacco smoking is a recognized major risk factor for lung tumor development. We analyzed the effect of tobacco-specific nitrosamines (TSNAs) on human lung adenocarcinoma metabolic reprogramming, an emergent hallmark of carcinogenesis.

Results: A series of in vitro and in vivo bioenergetic, proteomic, metabolomic and tumor biology studies were performed to analyze changes in lung cancer cell metabolism and the consequences for hallmarks of cancer, including tumor growth, cancer cell invasion and redox signaling. The findings revealed that nitrosamine ketone (NNK) stimulates mitochondrial function and promotes lung tumor growth in vivo. These malignant properties were acquired from the induction of mitochondrial biogenesis induced by the upregulation and activation of the beta-adrenergic receptor (β2-AR)-nicotinic acetylcholine receptor subunit alpha-7 (CHRNAα7)-dependent nitrosamine canonical signaling pathway. The observed NNK metabolic effects were mediated by TFAM overexpression and revealed a key role for mitochondrial reactive oxygen species (mtROS) and Annexin A1 in tumor growth promotion. Conversely, ectopic expression of the mitochondrial antioxidant enzyme manganese superoxide dismutase (MnSOD) rescued the reprogramming and malignant metabolic effects of exposure to NNK and overexpression of TFAM, underlining the link between NNK and mitochondrial redox signaling in lung cancer.

Innovation: Our findings describe the metabolic changes caused by NNK in a mechanistic framework for understanding how cigarette smoking causes lung cancer.

Conclusion: Mitochondria play a role in the promotion of lung cancer induced by tobacco-specific nitrosamines.

A key issue when designing clinical trials is the estimation of the number of subjects required. Assuming for multicenter trials or biomarker-stratified designs that the effect size between treatment arms is the same among the whole study population might be inappropriate. Limited work is available for properly determining the sample size for such trials. However, we need to account for both, the heterogeneity of the baseline hazards over clusters or strata but also the heterogeneity of the treatment effects, otherwise sample size estimates might be biased. Most existing methods account for either heterogeneous baseline hazards or treatment effects but they dot not allow to simultaneously account for both sources of variations. This article proposes an approach to calculate sample size formula for clustered or stratified survival data relying on frailty models. Both theoretical derivations and simulation results show the proposed approach can guarantee the desired power in worst case scenarios and is often much more efficient than existing approaches. Application to a real clinical trial designs is also illustrated.

Objectives: More than half of cancer patients require palliative care; however, inequality in access and late referral in the illness trajectory are major issues. This study assessed the cumulative incidence of first hospital-based palliative care (HPC) referral, as well as the influence of patient-, tumor-, and care-related factors.

Study design: This is a retrospective population-based study.

Methods: The study included patients from the 2014 population-based cancer registry of Gironde, France. International Classification of Diseases, Tenth Revision, coding for palliative care identified HPC referrals from 2014 to 2018. The study included 8424 patients. Analyses considered the competing risk of death and were stratified by initial cancer prognosis (favorable vs unfavorable [if metastatic or progressive cancer]).

Results: The 4-year incidence of HPC was 16.7% (95% confidence interval, 16.6-16.8). Lung cancer led to more referrals, whereas breast, colorectal, and prostatic locations were associated to less frequent HPC compared with other solid tumors. Favorable prognosis central nervous system tumors and unfavorable prognosis hematological malignancies also showed less HPC. The incidence of HPC was higher in tertiary centers, particularly for older patients. In the favorable prognosis subgroup, older and non-deprived patients received more HPC. In the unfavorable prognosis subgroup, the incidence of HPC was lower in patients who lived in rural areas than those who lived in urban areas.

Conclusions: One-sixth of cancer patients require HPC. Some factors influencing referral depend on the initial cancer prognosis. Our findings support actions to improve accessibility, especially for deprived patients, people living in rural areas, those with hematological malignancies, and those treated outside tertiary centers. In addition, consideration of age as factor of HPC may allow for improved design of the referral system.

Background: Guidelines recommend an early access to specialised palliative medicine services for patients with cancer, but studies have reported a continued underuse. Palliative care facilities deliver early care, alongside antineoplastic treatments, whereas hospice care structures intervene lately, when cancer-modifying treatments stop.

Aim: This review identified factors associated with early and late interventions of specialised services, by considering the type of structures studied (palliative vs hospice care).

Design: We performed a systematic review, prospectively registered on PROSPERO (ID: CRD42018110063).

Data sources: We searched Medline and Scopus databases for population-based studies. Two independent reviewers extracted the data and assessed the study quality using Joanna Briggs Institute critical appraisal checklists.

Results: The 51 included articles performed 67 analyses. Most were based on retrospective cohorts and US populations. The median quality scores were 19/22 for cohorts and 15/16 for cross-sectional studies. Most analyses focused on hospice care (n=37). Older patients, men, people with haematological cancer or treated in small centres had less specialised interventions. Palliative and hospice facilities addressed different populations. Older patients received less palliative care but more hospice care. Patients with high-stage tumours had more palliative care while women and patients with a low comorbidity burden received more hospice care.

Conclusion: Main disparities concerned older patients, men and people with haematological cancer. We highlighted the challenges of early interventions for older patients and of late deliveries for men and highly comorbid patients. Additional data on non-American populations, outpatients and factors related to quality of life and socioeconomic status are needed.