On null hypotheses in survival analysis

Changes in Presentation, Treatment, and Survival of Patients with Hepatocellular Carcinoma in Damietta, Egypt, 2007-2019: A Retrospective Monocentric Cohort Study

Introduction

We aimed to assess temporal changes in the presentation and survival of patients with hepatocellular carcinoma (HCC) in the northern Egypt region, one of the regions reporting the highest incidence of the disease globally.

Methods

We conducted a monocentric retrospective study. Patients presenting at the Damietta Oncology referral center between 2007 and 2019 with a diagnosed HCC were eligible. Individual, clinical and tumor characteristics at HCC diagnosis, including the Barcelona Clinic Liver Cancer (BCLC) staging, were retrieved from medical files and patients' final vital status was ascertained by combining various data sources. Patients were divided into 2 groups based on diagnosis period: pre- and post-2014. Survival was analysed based on Kaplan-Meier curves and differences in restricted mean survival time (RMST).

Results

Data from 5097 patients (among 5210 eligible, 97.8%) were analyzed. We observed a significant trend toward HCC diagnosed at earlier stage in the post- vs pre-2014 period (BCLC stage 0/A or B: 37.2% vs 27.1%, p<10^-3). Overall patient's survival after the HCC diagnosis was poor, with a median of 8.1 months. The BCLC staging system performed well in predicting survival. Despite a trend toward HCC diagnosed at earlier stages, we did not observe a significant improvement in survival over time. Overall, treatments offered in this medical center were in line with international guidelines, and 16.1% of the patients who received a curative treatment had an improved survival (30.7 months in median). However, HCC recurrence was frequent among patients cured for HCC, with a median time to recurrence of 22 months.

Discussion

Overall survival after HCC diagnosis in Egypt remains poor but is significantly improved by curative therapy. Despite a trend toward earlier diagnosis of HCC, we did not observe a general improvement in survival over time, which remains to be clearly understood.

Prognosis of cancer survivors: estimation based on differential equations

We present a method for estimating several prognosis parameters for cancer survivors. The method utilizes the fact that these parameters solve differential equations driven by cumulative hazards. By expressing the parameters as solutions to differential equations, we develop generic estimators that are easy to implement with standard statistical software. We explicitly describe the estimators for prognosis parameters that are often employed in practice, but also for parameters that, to our knowledge, have not been used to evaluate prognosis. We then apply these parameters to assess the prognosis of five common cancers in Norway.

Occupational physical activity and longevity in working men and women in Norway: a prospective cohort study

BACKGROUND

Studies suggest that high occupational physical activity increases mortality risk. However, it is unclear whether this association is causal or can be explained by a complex network of socioeconomic and behavioural factors. We aimed to examine the association between occupational physical activity and longevity, taking a complex network of confounding variables into account.

METHODS

In this prospective cohort study, we linked data from Norwegian population-based health examination surveys, covering all parts of Norway with data from the National Population and Housing Censuses and the Norwegian Cause of Death Registry. 437 378 participants (aged 18-65 years; 48·7% men) self-reported occupational physical activity (mutually exclusive groups: sedentary, walking, walking and lifting, and heavy labour) and were followed up from study entry (between February, 1974, and November, 2002) to death or end of follow-up on Dec 31, 2018, whichever came first. We estimated differences in survival time (death from all causes, cardiovascular disease, and cancer) between occupational physical activity categories using flexible parametric survival models adjusted for confounding factors.

FINDINGS

During a median of 28 years (IQR 25-31) from study entry to the end of follow-up, 74 203 (17·0%) of the participants died (all-cause mortality), of which 20 111 (27·1%) of the deaths were due to cardiovascular disease and 29 886 (40·3%) were due to cancer. Crude modelling indicated shorter mean survival times among men in physically active occupations than in those with sedentary occupations. However, this finding was reversed following adjustment for confounding factors (birth cohort, education, income, ethnicity, prevalent cardiovascular disease, smoking, leisure-time physical activity, body-mass index), with estimates suggesting that men in occupations characterised by walking, walking and lifting, and heavy labour had life expectancies equivalent to 0·4 (95% CI -0·1 to 1·0), 0·8 (0·3 to 1·3), and 1·7 (1·2 to 2·3) years longer, respectively, than men in the sedentary referent category. Results for mortality from cardiovascular disease and cancer showed a similar pattern. No clear differences in survival times were observed between occupational physical activity groups in women.

INTERPRETATION

Our results suggest that moderate to high occupational physical activity contributes to longevity in men. However, occupational physical activity does not seem to affect longevity in women. These results might inform future physical activity guidelines for public health.

FUNDING

The Norwegian Research Council (grant number 249932/F20).

The additive hazard estimator is consistent for continuous-time marginal structural models

Marginal structural models (MSMs) allow for causal analysis of longitudinal data. The standard MSM is based on discrete time models, but the continuous-time MSM is a conceptually appealing alternative for survival analysis. In applied analyses, it is often assumed that the theoretical treatment weights are known, but these weights are usually unknown and must be estimated from the data. Here we provide a sufficient condition for continuous-time MSM to be consistent even when the weights are estimated, and we show how additive hazard models can be used to estimate such weights. Our results suggest that continuous-time weights perform better than IPTW when the underlying process is continuous. Furthermore, we may wish to transform effect estimates of hazards to other scales that are easier to interpret causally. We show that a general transformation strategy can be used on weighted cumulative hazard estimates to obtain a range of other parameters in survival analysis, and explain how this strategy can be applied on data using our R packages ahw and transform.hazards.