Cancer treatment overview

General aspects of cancer and its treatment are reviewed in the previous section. In most situations, planning proper cancer treatment requires adequate information on cancer staging, pathologic and molecular test results, imaging, laboratory results and patient factors such as comorbid conditions. Since several different treatment modalities may be utilized singly or in combination, input from several specialists may be necessary. Sometimes, treatment plan may have to be modified depending on tolerance and response to initial treatment.


Clinical research

Medications for potential treatment of human diseases are developed in various phases of research. First, chemical or biological molecules are identified based on various factors including their physical and chemical properties. Their biological activity and possible toxicity are then assessed using various pre-clinical (prior to testing on humans) studies including in animals and in tissue cultures. Computer modelling may be used.

Once a promising molecule is identified, it undergoes several phases of clinical research generally ranging phases 1 through 4. Each phase has specific purposes and limitations. Clinical trials may have different designs and may not always fit into a specific phase. This process from preclinical to drug approval may take several years. Clinical trials are highly regulated, expensive and are carefully designed to get most accurate information with least amount of bias possible.


Clinical trial results

Management of human diseases are guided by scientific or historical evidence that a treatment works and adequate knowledge of benefits vs risks. Such evidence may come from various forms of research. Results of scientific research are commonly presented and discussed in scientific conferences and/or published in various scientific publications many of which are indexed in PubMed. PubMed is a free search engine accessing primarily the MEDLINE database of references and abstracts on life sciences and biomedical topics. The United States National Library of Medicine (NLM) at the National Institutes of Health maintains the database as part of the Entrez system of information retrieval.


Limitations of clinical research

Research data, no matter how scientifically rigorous, will have many limitations. Such limitations may include patient factors (distribution of age, sex, race, comorbidities among study groups), study design (randomized, case control, epidemiological etc. each with its own advantages and limitations) and may other factors. A research study on a cancer type may have included all the molecular subtypes of that cancer which may respond differently for the same treatment. This data may overestimate the benefit for some subtypes while underestimating the benefits for the other subtypes. There are many forms of bias which also affect the data integrity.

Since all research data have inherent limitations, using these data for an individual adds additional bias and limitations. Clinical trial data is a collective wisdom based on population study. Individuals in the population have wide variety of individual variations in genetics, comorbidities, tolerance, response and personal preferences.While research data is currently the most scientific evidence based data available, this comes with significant limitations for individual use. Hence one has to be careful in interpreting scientific data for individual treatment.

It is important to note that each clinical research is done to answer a specific clinical question and not designed to compare the data to another trial. In many situations, we are presented with several treatment choices with many clinical research trials supporting those treatments. When only one treatment need to be chosen among many choices, these choices need to be compared overall for their benefits and risks to make the right choice.


Limitations of data

The data presented here are from clinical research (trials) done on adult (unless specified) patients and volunteers. These are select group of clinical trials which may provide scientific basis for use of specific medications or regimen as cancer treatment. When several trials are available for one treatment, only one or few may be presented. This database does not include all the available clinical trial results. Information of adverse effects and additional information is commonly presented with minimal or no modifications to improve accuracy. Reference link for the original source of data is provided. When using these data, always refer to the original data and original article for the most accurate and complete information. Information on drug data particularly newer agents are commonly obtained from drug monograph.

Even though the research trials are not designed to be comparable, when several treatment choices are available, we may need to analyze risks vs benefits in totality and compare/analyze to make right treatment choice. It is important to look at the data in totality and the clinical context rather than just compare number to number. There are several limitations in using the data presented here including limited number of data sets. Interpretation of enormous scientific data to make the right treatment choice requires professional expertise in conjunction with patient factors and preferences.

The intention of this effort is to present clinical trial data in an easy to visualize format so that a professional can look at available data side by side for easy comparison. Author/scientist's interpretations/opinions may be important and cannot be represented in numbers. Typographic errors can occur in data entry and/or in the original publication. When many data are presented in the original work, only major information may be presented here. Other data not presented here may be relevant for overall interpretation. Sometimes, research done on the same treatment or condition at different times or place may have different findings. All of them may be relevant in overall interpretation. However, only one or few may be presented here.

Treatment decisions should be made in consultation with a physician incorporating individual variables (comorbidities, tumor and personal genetics, tumor characteristics etc.) as well patient preferences. Financial aspects may have to be considered as well. Results of clinical trials are only one of many components in decision making. However, when several treatment options appear reasonable, research data may help to select a treatment that may have higher probability of helping and/or lower probability of harm.


How to use the data

Database can be searched based on disease, drug or regimen. Search box may also be used. Upon searching, research matching the selection is presented in a table format. Major treatment context, medication studied, disease type and other information is shown. Disease conditions and contexts are for adult population unless specified. Using this table, upto 4 specific trial can be selected for viewing data or comparison which are presented in a separate tab.

The selected research data is presented with information including cancer type, additional clinical context if available as well as major outcome measures. Select additional information which may help interpret data (data info), title of the study (Title), summary of side effects when available (ADRs) will popup when cursor hovers over appropriate label. Some trial data are presented in multiple places such as conference presentation, subsequent journal article, drug company data on file and possibly FDA approval data etc. When multiple related data sets are available in the database, link to related data sets is presented under "Related data".

The tern "control arm" is used to indicate either a control arm or a comparator arm. When a study do not identify a treatment arm as either control or a comparator arm, one of the arms will be designated as control arm.

Many commonly used outcome measures are presented using standard abbreviation. Explanations for abbreviations and terminology are presented to some extent under help links. It is important to note that absolute or visual difference between the two arms of the study may not correlate with statistical significance. A small difference which is visually may not be significant could be statistically significant. On the other hand a large difference visually may not be statistically significant. This happens due to differences in the number of patients, duration of follow up and other research related factors. Hence, final interpretation should not be made on visual impression alone.

While the intension is to provide easy visualization and understanding, please note significant limitations of data sets, interpretations and non-comparability. The data should be used by a qualified professional or in consultation with a qualified professional. Please also review disclaimers.