Some of the problems listed above can be overcome by conducting a (prospective) cohort study. At baseline, one starts with a cohort of people free from the outcome of interest. During or at the end of follow-up, incident cases in both the unexposed and the exposed groups are identified, and RRs or HRs can be calculated. Despite the theoretical advantages of a cohort design, there are some practical disadvantages. The cohort studies often need large sample sizes and/or long follow- ups to accumulate enough incident cases for meaningful analyses. These studies are often expensive. From a methodological point of view, the potential bias of (residual) confounding can never be totally excluded.

Randomized controlled trials are a specific type of cohort study. At the start of the study, participants are randomly assigned to the intervention group (treatment under investigation) or a control group (no treatment, placebo, or standard treatment). After the start of the treatment, patients often get better. This may be due to the treatment or other circumstances such as spontaneous resolution, effective co-interventions, and placebo effects. Only a sufficiently large, randomized, and blinded trial is useful to estimate the efficacy of drugs and other treatments. The best comparison is often between the new treatment and the best available one, not the sham treatment [15]. The randomization, if successful, ensures that confounding factors are evenly distributed between the intervention and control groups. As with the cohort studies, incident cases in both groups are determined during or at the end of follow-up, allowing for the risk estimates to be calculated.

For clinicians interested in evidence pertaining most directly to a particular class of patients, subgroup analyses can be very informative. The strength of evidence for subgroup effects depends on the question of whether hypotheses have been defined prior to analysis, whether potential problems regarding multiple comparisons have been considered, and whether there is biological plausibility of the effects found. Using these guidelines, the reader of a trial report should be able to decide if presented subgroup effects are of clinical importance or if the overall result is a better estimate of treatment effect [16].

In contrast to cohort studies, the starting point in case- control studies is not to assess the exposure status but the disease status. People with the disease of interest are selected, and a control group of people without the disease is subsequently recruited. The control group should include people from the same source population as the cases, implying that if any of the controls had developed the disease, they would have been eligible for inclusion in the study as a case.

The selection of a valid control group is important in case-control studies and has, therefore, generated a fair amount of discussion in the epidemiological literature. It is possible to select population controls, hospital controls, friends or relatives of patients, or any combination of these [17]. Case-control studies have the advantage of being relatively quick and inexpensive to conduct and are especially appealing in rare diseases. A disadvantage is the large potential for selection bias, especially in the recruitment of controls. In addition, there is also a real danger of information (recall) bias. Similar to cohort studies, bias by confounding can never be totally ruled out.

A pilot study is often performed before the start of a large study. Its aim is to improve the methodological quality and evaluate the feasibility. The estimate of the effect of an intervention in a pilot study is determined to a large extent by chance and, therefore, cannot be considered conclusive. However, the inclusion of such results in a later cumulative meta-analysis may lead to sufficient power to assess the efficacy of an experimental intervention [18].

In a systematic review, all available evidence (literature) on a certain topic is reviewed in a systematic, transparent, and reproducible manner. These studies can be especially useful when results from single studies are contradictory and/or have large confidence intervals due to a small sample size. When the studies in a systematic review are reasonably homogenous, their results can be pooled in meta-analyses. This results in one effect size for all the studies together, with a much smaller confidence interval than the individual studies. An example is a systematic review of the survival of patients with uveal melanoma treated with brachytherapy. The result of this meta-analysis showed that the 5-year melanoma- related mortality rate was 6% for small and medium tumors and 26% for large tumors [19].

Li J. A meta-analysis of the efficacy of intra-arterial chemotherapy for the management of retinoblastoma patients. Adv Clin Exp Med. 2023 Jul 24. doi: 10.17219/acem/166664)

A recently published meta-analysis of intraarterial chemotherapy for retinoblastoma revealed a high level of heterogeneity (I²=98% ) with an enucleation rate ranging from 0% to 44% . The estimated total pooled OR of enucleation rates was 0.53 (95% CI: 0.42-0.65, p<0.001) (Fig. 1.3) [20].

In general, ophthalmic tumors are rare compared to other ophthalmic diseases. Therefore, it is difficult to conduct large studies with enough power to get statistically significant and clinically relevant results. A large number of studies are published each year, most of which are descriptive, concerning retrospective patient series. To conduct randomized clinical trials, international collaboration is necessary to include enough patients in the different treatment arms of the study. Furthermore, uniform definitions and study methodology are very important to compare the different studies in the literature and to be able to perform systematic reviews and meta-analyses.