Reams could be written about this, but the simple warning is that readers or reviewers of papers have to be cautious of results of trials, especially where vote-counting is being done. But also beware the power of words. Even when statistical testing shows no difference, it is common to see the results hailed as a success. While that may sound silly when written down, even the most cynical of readers can be fooled into drawing the wrong conclusion. Abstracts are notorious for misleading in this way.
Data manipulation is a bit more complicated to detect.
An example would be an intervention where we are not told what the start condition of patients is, nor the end, but that at some time in between the rate of change was statistically significant by some test with which we are unfamiliar. Again, crucially important where vote counting is being done to determine whether the intervention works or not. Outcomes reported in trials are an even more sticky problem. It is not infrequent that surrogate measures are used rather than an outcome of real clinical importance. Unless these surrogate measures are known unequivocally to correlate with clinical outcomes of importance, then an unjust sense of effectiveness could be implied or assumed.