JNCI Journal of the National Cancer Institute最新文献

Background: Prognostic factors in resected pancreatic ductal adenocarcinoma (PDAC) have been determined under the assumption that hazard ratios (HRs) remain static. However, PDAC is a dynamic disease with evolving conditional survival. The aim of this study was to determine if the impact of prognostic factors in PDAC is time-varying.

Methods: This was a multicenter, retrospective cohort study of the prospectively maintained Dutch Pancreatic Cancer Recurrence Database and New York University and Johns Hopkins Hospital Institutional Databases. Patients with complete macroscopic resection of histopathologically proven PDAC between 2014 and 2019 and available follow-up data were included. The time-varying impact of prognostic factors identified by univariable Cox regression was modeled using Aalen's Additive Regression Models (Aalen's models) and visualized as plots of cumulative hazard.

Results: In total, 3104 patients were included, of whom 938 (30.2%) received neoadjuvant therapy (NAT), whereas the rest underwent upfront surgery (US). A total of 201 (6.5%) patients achieved observed long-term survival (>5 years). Aalen's models showed that lymphovascular invasion, perineural invasion, and nodal disease were prognostic up to 2 years postoperatively. At varying points thereafter, these variables lost their impact in the NAT but not US patients. Similarly, during the fourth year of follow-up, American Society of Anesthesiology scores became impactful in the NAT but not in the US patients.

Conclusion: The impact of prognostic factors in resected PDAC across NAT and US patients is time-varying. Our results suggest that aggressive disease drives early mortality but, after NAT, tumor-biological factors lose prognostic importance to frailty and comorbidities over time.

Introduction: There is convincing evidence that overall adiposity increases the risks of several cancers. Whether the distribution of adiposity plays a similar role is unclear.

Methods: We used 2-sample Mendelian randomization (MR) to examine causal relationships of 5 adiposity distribution traits (abdominal subcutaneous adipose tissue (ASAT); visceral adipose tissue (VAT); gluteofemoral adipose tissue (GFAT); liver fat; and pancreas fat) with the risks of 12 obesity-related cancers (endometrial, ovarian, breast, colorectal, pancreas, multiple myeloma, liver, kidney (renal cell), thyroid, gallbladder, esophageal adenocarcinoma, and meningioma).

Results: Sample size across all genome-wide association studies (GWAS) ranged from 8407 to 728 896 (median: 57 249). We found evidence that higher genetically predicted ASAT increased the risks of endometrial cancer, liver cancer, and esophageal adenocarcinoma (odds ratios (OR) and 95% confidence intervals (CI) per standard deviation (SD) higher ASAT = 1.79 (1.18 to 2.71), 3.83 (1.39 to 10.53), and 2.34 (1.15 to 4.78), respectively). Conversely, we found evidence that higher genetically predicted GFAT decreased the risks of breast cancer and meningioma (ORs and 95% CIs per SD higher genetically predicted GFAT = 0.77 (0.62 to 0.97) and 0.53 (0.32 to 0.90), respectively). We also found evidence for an effect of higher genetically predicted VAT and liver fat on increased liver cancer risk (ORs and 95% CIs per SD higher genetically predicted adiposity trait = 4.29 (1.41 to 13.07) and 4.09 (2.29 to 7.28), respectively).

Discussion: Our analyses provide novel insights into the relationship between adiposity distribution and cancer risk. These insights highlight the potential importance of adipose tissue distribution alongside maintaining a healthy weight for cancer prevention.

Background: Treatment exposure-based risk-stratification of long-term cancer survivors may help inform health care in survivorship clinics. We used the large, diverse population of the Childhood Cancer Survivor Study to test a modified, exposure-based strata previously developed within United Kingdom to classify survivors with respect to risk of late morbidity and health-related mortality.

Methods: Five-year survivors of childhood cancer were categorized into low-, medium-, and high-risk groups based on treatment exposures and diagnosis. Primary endpoints included cumulative health-related (ie, nonrecurrence, nonexternal) late mortality and cumulative incidence of severe or fatal (CTCAE grade 3-5) chronic health conditions conditional on reaching age 20 without the outcome. Siblings were a comparison group for chronic health conditions. Cox proportional hazards models were adjusted for sex, race, ethnicity, and age at diagnosis.

Results: Among 15,346 survivors diagnosed 1970-1999, the risk of developing a severe chronic condition by age 35 was 11.9% (95% confidence interval [CI] = 9.9% to 14.3%), 15.1% (13.7% to 16.6%), and 25.4% (24.3% to 26.5%) for low-, medium-, and high-risk survivors, respectively, and 6.9% (6.1% to 7.9%) for siblings. Multivariable analysis confirmed higher likelihood of developing a chronic condition in high (hazard ratio [HR] = 2.9, 2.5 to 3.4) and medium (HR = 1.5, 1.3 to 1.8) versus the low-risk group. Health-related mortality was similarly increased among high (HR = 5.1, 3.8 to 7.0) and medium (HR = 2.5, 1.8 to 3.4) risk groups, as well as Black versus Non-Hispanic White survivors (HR = 1.7, 1.3 to 2.1).

Conclusions: Exposure-based risk categorizations can provide generalized risk stratification regarding future chronic health conditions and early mortality and may be useful in guiding management of childhood cancer survivors.

Background: With the increasing popularity of decorative tattooing, which entails the intradermal injection of inks that may contain carcinogens, investigating the related potential skin cancer risk is a public health priority.

Methods: We used data from the Cancer Risk Attributable with the Body Art of Tattooing (CRABAT) study, nested in the French national cohort Constances (adults aged 18-69 years recruited in 2012-2018). Tattoo exposure was collected in 2020-23. Skin cancers overall, cutaneous melanoma (CM), and non-melanoma skin cancer (NMSC) diagnosed during 2007-2021 were retrieved from national health insurance data. As exposure was collected after possible disease ascertainment, risks of skin cancer with prior tattoo exposure were assessed using logistic regression and Cox proportional hazards models in a retrospective cohort design.

Results: Among 111074 participants, 1789 skin cancers (1.6%) were recorded (693 CM, 1096 NMSC). No association was found between binary tattoo exposure (yes/no) and any skin cancer type. In the highest exposure category of tattoo body surface (>2 hand palms), 2 cases were observed among 1633 participants (0.1%), yielding an odds ratio of 0.21 for overall skin cancer (95% CI: 0.05-0.83; reference no tattoos); however, the corresponding Cox model was not significant (HR = 0.26, 95% CI: 0.07-1.05).

Conclusion: No overall association between tattoo exposure and skin cancer was observed. The inverse association in the highest exposure category is based on very few cases and should be interpreted with caution. Further studies with larger case numbers and more detailed exposure assessment are warranted.